📄 CodeRabbit inference engine (.github/.coderabbit_review_guide.md)

**/*.{cu,cuh,cpp,hpp,h}: Track GPU device memory allocations and deallocations to prevent memory leaks; ensure cudaMalloc/cudaFree balance and cleanup of streams/events
Validate algorithm correctness in optimization logic: simplex pivots, branch-and-bound decisions, routing heuristics, and constraint/objective handling must produce correct results
Check numerical stability: prevent overflow/underflow, precision loss, division by zero/near-zero, and use epsilon comparisons for floating-point equality checks
Validate correct initialization of variable bounds, constraint coefficients, and algorithm state before solving; ensure reset when transitioning between algorithm phases (presolve, simplex, diving, crossover)
Ensure variables and constraints are accessed from the correct problem context (original vs presolve vs folded vs postsolve); verify index mapping consistency across problem transformations
For concurrent CUDA operations (barriers, async operations), explicitly create and manage dedicated streams instead of reusing the default stream; document stream lifecycle
Eliminate unnecessary host-device synchronization (cudaDeviceSynchronize) in hot paths that blocks GPU pipeline; use streams and events for async execution
Assess algorithmic complexity for large-scale problems (millions of variables/constraints); ensure O(n log n) or better complexity, not O(n²) or worse
Verify correct problem size checks before expensive GPU/CPU operations; prevent resource exhaustion on oversized problems
Identify assertions with overly strict numerical tolerances that fail on legitimate degenerate/edge cases (near-zero pivots, singular matrices, empty problems)
Ensure race conditions are absent in multi-GPU code and multi-threaded server implementations; verify proper synchronization of shared state
Refactor code duplication in solver components (3+ occurrences) into shared utilities; for GPU kernels, use templated device functions to avoid duplication
Check that hard-coded GPU de...

Files:

• cpp/src/dual_simplex/basis_updates.hpp
• cpp/src/dual_simplex/bounds_strengthening.cpp
• cpp/src/dual_simplex/basis_solves.hpp
• cpp/src/dual_simplex/logger.hpp
• cpp/src/mip/diversity/recombiners/sub_mip.cuh
• cpp/src/mip/diversity/lns/rins.cu
• cpp/src/mip/solver.cu
• cpp/src/dual_simplex/primal.cpp
• cpp/src/dual_simplex/mip_node.hpp
• cpp/src/dual_simplex/crossover.cpp
• cpp/src/dual_simplex/basis_updates.cpp
• cpp/src/dual_simplex/simplex_solver_settings.hpp
• cpp/src/dual_simplex/pseudo_costs.hpp
• cpp/src/dual_simplex/basis_solves.cpp
• cpp/src/dual_simplex/diving_heuristics.hpp
• cpp/src/dual_simplex/pseudo_costs.cpp
• cpp/src/dual_simplex/phase2.cpp
• cpp/src/dual_simplex/diving_heuristics.cpp
• cpp/src/dual_simplex/node_queue.hpp
• cpp/src/dual_simplex/branch_and_bound.hpp
• cpp/src/dual_simplex/branch_and_bound.cpp

📄 CodeRabbit inference engine (.github/.coderabbit_review_guide.md)

Verify C API does not break ABI stability (no struct layout changes, field reordering); maintain backward compatibility in Python and server APIs with deprecation warnings

Files:

• cpp/src/dual_simplex/basis_updates.hpp
• cpp/src/dual_simplex/basis_solves.hpp
• cpp/src/dual_simplex/logger.hpp
• cpp/src/dual_simplex/mip_node.hpp
• cpp/src/dual_simplex/simplex_solver_settings.hpp
• cpp/src/dual_simplex/pseudo_costs.hpp
• cpp/src/dual_simplex/diving_heuristics.hpp
• cpp/src/dual_simplex/node_queue.hpp
• cpp/src/dual_simplex/branch_and_bound.hpp

📄 CodeRabbit inference engine (.github/.coderabbit_review_guide.md)

**/*.{cpp,hpp,h}: Check for unclosed file handles when reading MPS/QPS problem files; ensure RAII patterns or proper cleanup in exception paths
Validate input sanitization to prevent buffer overflows and resource exhaustion attacks; avoid unsafe deserialization of problem files
Prevent thread-unsafe use of global and static variables; use proper mutex/synchronization in server code accessing shared solver state

Files:

• cpp/src/dual_simplex/basis_updates.hpp
• cpp/src/dual_simplex/bounds_strengthening.cpp
• cpp/src/dual_simplex/basis_solves.hpp
• cpp/src/dual_simplex/logger.hpp
• cpp/src/dual_simplex/primal.cpp
• cpp/src/dual_simplex/mip_node.hpp
• cpp/src/dual_simplex/crossover.cpp
• cpp/src/dual_simplex/basis_updates.cpp
• cpp/src/dual_simplex/simplex_solver_settings.hpp
• cpp/src/dual_simplex/pseudo_costs.hpp
• cpp/src/dual_simplex/basis_solves.cpp
• cpp/src/dual_simplex/diving_heuristics.hpp
• cpp/src/dual_simplex/pseudo_costs.cpp
• cpp/src/dual_simplex/phase2.cpp
• cpp/src/dual_simplex/diving_heuristics.cpp
• cpp/src/dual_simplex/node_queue.hpp
• cpp/src/dual_simplex/branch_and_bound.hpp
• cpp/src/dual_simplex/branch_and_bound.cpp

📄 CodeRabbit inference engine (.github/.coderabbit_review_guide.md)

Avoid inappropriate use of exceptions in performance-critical GPU operation paths; prefer error codes or CUDA error checking for latency-sensitive code

Files:

• cpp/src/dual_simplex/basis_updates.hpp
• cpp/src/dual_simplex/bounds_strengthening.cpp
• cpp/src/dual_simplex/basis_solves.hpp
• cpp/src/dual_simplex/logger.hpp
• cpp/src/mip/diversity/lns/rins.cu
• cpp/src/mip/solver.cu
• cpp/src/dual_simplex/primal.cpp
• cpp/src/dual_simplex/mip_node.hpp
• cpp/src/dual_simplex/crossover.cpp
• cpp/src/dual_simplex/basis_updates.cpp
• cpp/src/dual_simplex/simplex_solver_settings.hpp
• cpp/src/dual_simplex/pseudo_costs.hpp
• cpp/src/dual_simplex/basis_solves.cpp
• cpp/src/dual_simplex/diving_heuristics.hpp
• cpp/src/dual_simplex/pseudo_costs.cpp
• cpp/src/dual_simplex/phase2.cpp
• cpp/src/dual_simplex/diving_heuristics.cpp
• cpp/src/dual_simplex/node_queue.hpp
• cpp/src/dual_simplex/branch_and_bound.hpp
• cpp/src/dual_simplex/branch_and_bound.cpp

📄 CodeRabbit inference engine (.github/.coderabbit_review_guide.md)

**/*.{cu,cuh}: Every CUDA kernel launch and memory operation must have error checking with CUDA_CHECK or equivalent verification
Avoid reinventing functionality already available in Thrust, CCCL, or RMM libraries; prefer standard library utilities over custom implementations

Files:

• cpp/src/mip/diversity/recombiners/sub_mip.cuh
• cpp/src/mip/diversity/lns/rins.cu
• cpp/src/mip/solver.cu

📄 CodeRabbit inference engine (.github/.coderabbit_review_guide.md)

**/*.cu: Verify race conditions and correctness of GPU kernel shared memory, atomics, and warp-level operations
Detect inefficient GPU kernel launches with low occupancy or poor memory access patterns; optimize for coalesced memory access and minimize warp divergence in hot paths

Files:

• cpp/src/mip/diversity/lns/rins.cu
• cpp/src/mip/solver.cu

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Reduce tight coupling between solver components (presolve, simplex, basis, barrier); increase modularity and reusability of optimization algorithms

Applied to files:

• cpp/src/dual_simplex/basis_updates.hpp
• cpp/src/dual_simplex/bounds_strengthening.cpp
• cpp/src/dual_simplex/basis_solves.hpp
• cpp/src/mip/solver.cu
• cpp/src/dual_simplex/primal.cpp
• cpp/src/dual_simplex/crossover.cpp
• cpp/src/dual_simplex/basis_updates.cpp
• cpp/src/dual_simplex/simplex_solver_settings.hpp
• cpp/src/dual_simplex/basis_solves.cpp
• cpp/src/dual_simplex/phase2.cpp
• cpp/src/dual_simplex/branch_and_bound.hpp
• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Validate correct initialization of variable bounds, constraint coefficients, and algorithm state before solving; ensure reset when transitioning between algorithm phases (presolve, simplex, diving, crossover)

Applied to files:

• cpp/src/dual_simplex/basis_updates.hpp
• cpp/src/dual_simplex/bounds_strengthening.cpp
• cpp/src/dual_simplex/basis_solves.hpp
• cpp/src/mip/diversity/recombiners/sub_mip.cuh
• cpp/src/dual_simplex/CMakeLists.txt
• cpp/src/mip/diversity/lns/rins.cu
• cpp/src/mip/solver.cu
• cpp/src/dual_simplex/primal.cpp
• cpp/src/dual_simplex/mip_node.hpp
• cpp/src/dual_simplex/crossover.cpp
• cpp/src/dual_simplex/basis_updates.cpp
• cpp/src/dual_simplex/simplex_solver_settings.hpp
• cpp/src/dual_simplex/basis_solves.cpp
• cpp/src/dual_simplex/diving_heuristics.hpp
• cpp/src/dual_simplex/pseudo_costs.cpp
• cpp/src/dual_simplex/phase2.cpp
• cpp/src/dual_simplex/diving_heuristics.cpp
• cpp/src/dual_simplex/branch_and_bound.hpp
• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Validate algorithm correctness in optimization logic: simplex pivots, branch-and-bound decisions, routing heuristics, and constraint/objective handling must produce correct results

Applied to files:

• cpp/src/dual_simplex/basis_updates.hpp
• cpp/src/dual_simplex/bounds_strengthening.cpp
• cpp/src/dual_simplex/basis_solves.hpp
• cpp/src/dual_simplex/CMakeLists.txt
• cpp/src/mip/diversity/lns/rins.cu
• cpp/src/mip/solver.cu
• cpp/src/dual_simplex/primal.cpp
• cpp/src/dual_simplex/crossover.cpp
• cpp/src/dual_simplex/basis_updates.cpp
• cpp/src/dual_simplex/simplex_solver_settings.hpp
• cpp/src/dual_simplex/pseudo_costs.hpp
• cpp/src/dual_simplex/basis_solves.cpp
• cpp/src/dual_simplex/diving_heuristics.hpp
• cpp/src/dual_simplex/pseudo_costs.cpp
• cpp/src/dual_simplex/phase2.cpp
• cpp/src/dual_simplex/diving_heuristics.cpp
• cpp/src/dual_simplex/node_queue.hpp
• cpp/src/dual_simplex/branch_and_bound.hpp
• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Ensure variables and constraints are accessed from the correct problem context (original vs presolve vs folded vs postsolve); verify index mapping consistency across problem transformations

Applied to files:

• cpp/src/dual_simplex/bounds_strengthening.cpp
• cpp/src/mip/solver.cu
• cpp/src/dual_simplex/crossover.cpp
• cpp/src/dual_simplex/basis_solves.cpp
• cpp/src/dual_simplex/diving_heuristics.hpp
• cpp/src/dual_simplex/pseudo_costs.cpp
• cpp/src/dual_simplex/phase2.cpp
• cpp/src/dual_simplex/diving_heuristics.cpp
• cpp/src/dual_simplex/branch_and_bound.hpp
• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*test*.{cpp,cu,py} : Add tests for algorithm phase transitions: verify correct initialization of bounds and state when transitioning from presolve to simplex to diving to crossover

Applied to files:

• cpp/src/dual_simplex/bounds_strengthening.cpp
• cpp/src/dual_simplex/CMakeLists.txt
• cpp/src/mip/diversity/lns/rins.cu
• cpp/src/mip/solver.cu
• cpp/src/dual_simplex/primal.cpp
• cpp/src/dual_simplex/crossover.cpp
• cpp/src/dual_simplex/basis_updates.cpp
• cpp/src/dual_simplex/simplex_solver_settings.hpp
• cpp/src/dual_simplex/basis_solves.cpp
• cpp/src/dual_simplex/diving_heuristics.hpp
• cpp/src/dual_simplex/phase2.cpp
• cpp/src/dual_simplex/diving_heuristics.cpp
• cpp/src/dual_simplex/branch_and_bound.hpp
• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Identify assertions with overly strict numerical tolerances that fail on legitimate degenerate/edge cases (near-zero pivots, singular matrices, empty problems)

Applied to files:

• cpp/src/dual_simplex/bounds_strengthening.cpp
• cpp/src/dual_simplex/basis_solves.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*test*.{cpp,cu,py} : Test with free variables, singleton problems, and extreme problem dimensions near resource limits to validate edge case handling

Applied to files:

• cpp/src/dual_simplex/bounds_strengthening.cpp
• cpp/src/dual_simplex/CMakeLists.txt

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Assess algorithmic complexity for large-scale problems (millions of variables/constraints); ensure O(n log n) or better complexity, not O(n²) or worse

Applied to files:

• cpp/src/dual_simplex/bounds_strengthening.cpp
• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Refactor code duplication in solver components (3+ occurrences) into shared utilities; for GPU kernels, use templated device functions to avoid duplication

Applied to files:

• cpp/src/dual_simplex/CMakeLists.txt
• cpp/src/mip/diversity/lns/rins.cu
• cpp/src/mip/solver.cu
• cpp/src/dual_simplex/simplex_solver_settings.hpp
• cpp/src/dual_simplex/diving_heuristics.hpp
• cpp/src/dual_simplex/diving_heuristics.cpp
• cpp/src/dual_simplex/node_queue.hpp
• cpp/src/dual_simplex/branch_and_bound.hpp
• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh} : Avoid reinventing functionality already available in Thrust, CCCL, or RMM libraries; prefer standard library utilities over custom implementations

Applied to files:

• cpp/src/dual_simplex/CMakeLists.txt

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Check that hard-coded GPU device IDs and resource limits are made configurable; abstract multi-backend support for different CUDA versions

Applied to files:

• cpp/src/dual_simplex/CMakeLists.txt
• cpp/src/mip/diversity/lns/rins.cu
• cpp/src/mip/solver.cu

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Verify correct problem size checks before expensive GPU/CPU operations; prevent resource exhaustion on oversized problems

Applied to files:

• cpp/src/dual_simplex/CMakeLists.txt

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Track GPU device memory allocations and deallocations to prevent memory leaks; ensure cudaMalloc/cudaFree balance and cleanup of streams/events

Applied to files:

• cpp/src/dual_simplex/CMakeLists.txt

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*benchmark*.{cpp,cu,py} : Include performance benchmarks and regression detection for GPU operations; verify near real-time performance on million-variable problems

Applied to files:

• cpp/src/dual_simplex/CMakeLists.txt

Learnt from: chris-maes
Repo: NVIDIA/cuopt PR: 602
File: cpp/src/linear_programming/solve.cu:732-742
Timestamp: 2025-12-04T20:09:09.264Z
Learning: In cpp/src/linear_programming/solve.cu, the barrier solver does not currently return INFEASIBLE or UNBOUNDED status. It only returns OPTIMAL, TIME_LIMIT, NUMERICAL_ISSUES, or CONCURRENT_LIMIT.

Applied to files:

• cpp/src/mip/solver.cu
• cpp/src/dual_simplex/diving_heuristics.hpp
• cpp/src/dual_simplex/phase2.cpp
• cpp/src/dual_simplex/diving_heuristics.cpp
• cpp/src/dual_simplex/branch_and_bound.hpp
• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cpp,hpp,h} : Prevent thread-unsafe use of global and static variables; use proper mutex/synchronization in server code accessing shared solver state

Applied to files:

• cpp/src/mip/solver.cu
• cpp/src/dual_simplex/pseudo_costs.cpp

Learnt from: chris-maes
Repo: NVIDIA/cuopt PR: 500
File: cpp/src/dual_simplex/scaling.cpp:68-76
Timestamp: 2025-12-04T04:11:12.640Z
Learning: In the cuOPT dual simplex solver, CSR/CSC matrices (including the quadratic objective matrix Q) are required to have valid dimensions and indices by construction. Runtime bounds checking in performance-critical paths like matrix scaling is avoided to prevent slowdowns. Validation is performed via debug-only check_matrix() calls wrapped in #ifdef CHECK_MATRIX.

Applied to files:

• cpp/src/dual_simplex/basis_solves.cpp
• cpp/src/dual_simplex/branch_and_bound.hpp

cpp/src/dual_simplex/presolve.cpp (3)

• lower (240-240)
• upper (85-85)
• upper (241-241)

cpp/src/dual_simplex/simplex_solver_settings.hpp (2)

• log_filename (99-99)
• log_filename (99-99)

cpp/src/dual_simplex/basis_solves.cpp (3)

• basis_repair (614-675)
• basis_repair (614-622)
• basis_repair (860-868)

cpp/src/dual_simplex/basis_solves.hpp (1)

• basis_repair (43-51)

cpp/src/dual_simplex/basis_solves.cpp (3)

• basis_repair (614-675)
• basis_repair (614-622)
• basis_repair (860-868)

cpp/src/dual_simplex/basis_solves.hpp (1)

• basis_repair (43-51)

cpp/src/dual_simplex/basis_solves.cpp (3)

• basis_repair (614-675)
• basis_repair (614-622)
• basis_repair (860-868)

cpp/src/dual_simplex/basis_solves.hpp (1)

• basis_repair (43-51)

cpp/src/dual_simplex/basis_updates.hpp (1)

• A (374-380)

cpp/src/dual_simplex/presolve.cpp (3)

• lower (240-240)
• upper (85-85)
• upper (241-241)

cpp/src/dual_simplex/pseudo_costs.hpp (2)

• fractional (46-49)
• fractional (51-52)

cpp/src/dual_simplex/simplex_solver_settings.hpp (2)

• log (98-98)
• log (100-100)

cpp/src/dual_simplex/pseudo_costs.hpp (2)

• fractional (46-49)
• fractional (51-52)

cpp/src/dual_simplex/primal.cpp (2)

• primal_infeasibility (202-240)
• primal_infeasibility (202-205)

cpp/src/dual_simplex/mip_node.hpp (4)

• lower (97-108)
• lower (97-99)
• lower (112-130)
• lower (112-114)

cpp/src/dual_simplex/node_queue.hpp (4)

• node (21-25)
• node (21-21)
• node (27-31)
• node (27-27)

📄 CodeRabbit inference engine (.github/.coderabbit_review_guide.md)

**/*.{cu,cuh,cpp,hpp,h}: Track GPU device memory allocations and deallocations to prevent memory leaks; ensure cudaMalloc/cudaFree balance and cleanup of streams/events
Validate algorithm correctness in optimization logic: simplex pivots, branch-and-bound decisions, routing heuristics, and constraint/objective handling must produce correct results
Check numerical stability: prevent overflow/underflow, precision loss, division by zero/near-zero, and use epsilon comparisons for floating-point equality checks
Validate correct initialization of variable bounds, constraint coefficients, and algorithm state before solving; ensure reset when transitioning between algorithm phases (presolve, simplex, diving, crossover)
Ensure variables and constraints are accessed from the correct problem context (original vs presolve vs folded vs postsolve); verify index mapping consistency across problem transformations
For concurrent CUDA operations (barriers, async operations), explicitly create and manage dedicated streams instead of reusing the default stream; document stream lifecycle
Eliminate unnecessary host-device synchronization (cudaDeviceSynchronize) in hot paths that blocks GPU pipeline; use streams and events for async execution
Assess algorithmic complexity for large-scale problems (millions of variables/constraints); ensure O(n log n) or better complexity, not O(n²) or worse
Verify correct problem size checks before expensive GPU/CPU operations; prevent resource exhaustion on oversized problems
Identify assertions with overly strict numerical tolerances that fail on legitimate degenerate/edge cases (near-zero pivots, singular matrices, empty problems)
Ensure race conditions are absent in multi-GPU code and multi-threaded server implementations; verify proper synchronization of shared state
Refactor code duplication in solver components (3+ occurrences) into shared utilities; for GPU kernels, use templated device functions to avoid duplication
Check that hard-coded GPU de...

Files:

• cpp/src/dual_simplex/simplex_solver_settings.hpp
• cpp/src/mip/diversity/lns/rins.cu
• cpp/src/dual_simplex/pseudo_costs.cpp
• cpp/src/dual_simplex/node_queue.hpp
• cpp/src/dual_simplex/diving_heuristics.hpp
• cpp/src/dual_simplex/branch_and_bound.cpp
• cpp/src/dual_simplex/pseudo_costs.hpp
• cpp/src/dual_simplex/branch_and_bound.hpp
• cpp/src/dual_simplex/diving_heuristics.cpp

📄 CodeRabbit inference engine (.github/.coderabbit_review_guide.md)

Verify C API does not break ABI stability (no struct layout changes, field reordering); maintain backward compatibility in Python and server APIs with deprecation warnings

Files:

• cpp/src/dual_simplex/simplex_solver_settings.hpp
• cpp/src/dual_simplex/node_queue.hpp
• cpp/src/dual_simplex/diving_heuristics.hpp
• cpp/src/dual_simplex/pseudo_costs.hpp
• cpp/src/dual_simplex/branch_and_bound.hpp

📄 CodeRabbit inference engine (.github/.coderabbit_review_guide.md)

**/*.{cpp,hpp,h}: Check for unclosed file handles when reading MPS/QPS problem files; ensure RAII patterns or proper cleanup in exception paths
Validate input sanitization to prevent buffer overflows and resource exhaustion attacks; avoid unsafe deserialization of problem files
Prevent thread-unsafe use of global and static variables; use proper mutex/synchronization in server code accessing shared solver state

Files:

• cpp/src/dual_simplex/simplex_solver_settings.hpp
• cpp/src/dual_simplex/pseudo_costs.cpp
• cpp/src/dual_simplex/node_queue.hpp
• cpp/src/dual_simplex/diving_heuristics.hpp
• cpp/src/dual_simplex/branch_and_bound.cpp
• cpp/src/dual_simplex/pseudo_costs.hpp
• cpp/src/dual_simplex/branch_and_bound.hpp
• cpp/src/dual_simplex/diving_heuristics.cpp

📄 CodeRabbit inference engine (.github/.coderabbit_review_guide.md)

Avoid inappropriate use of exceptions in performance-critical GPU operation paths; prefer error codes or CUDA error checking for latency-sensitive code

Files:

• cpp/src/dual_simplex/simplex_solver_settings.hpp
• cpp/src/mip/diversity/lns/rins.cu
• cpp/src/dual_simplex/pseudo_costs.cpp
• cpp/src/dual_simplex/node_queue.hpp
• cpp/src/dual_simplex/diving_heuristics.hpp
• cpp/src/dual_simplex/branch_and_bound.cpp
• cpp/src/dual_simplex/pseudo_costs.hpp
• cpp/src/dual_simplex/branch_and_bound.hpp
• cpp/src/dual_simplex/diving_heuristics.cpp

📄 CodeRabbit inference engine (.github/.coderabbit_review_guide.md)

**/*.{cu,cuh}: Every CUDA kernel launch and memory operation must have error checking with CUDA_CHECK or equivalent verification
Avoid reinventing functionality already available in Thrust, CCCL, or RMM libraries; prefer standard library utilities over custom implementations

Files:

• cpp/src/mip/diversity/lns/rins.cu

📄 CodeRabbit inference engine (.github/.coderabbit_review_guide.md)

**/*.cu: Verify race conditions and correctness of GPU kernel shared memory, atomics, and warp-level operations
Detect inefficient GPU kernel launches with low occupancy or poor memory access patterns; optimize for coalesced memory access and minimize warp divergence in hot paths

Files:

• cpp/src/mip/diversity/lns/rins.cu

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Validate correct initialization of variable bounds, constraint coefficients, and algorithm state before solving; ensure reset when transitioning between algorithm phases (presolve, simplex, diving, crossover)

Applied to files:

• cpp/src/dual_simplex/simplex_solver_settings.hpp
• cpp/src/mip/diversity/lns/rins.cu
• cpp/src/dual_simplex/pseudo_costs.cpp
• cpp/src/dual_simplex/node_queue.hpp
• cpp/src/dual_simplex/diving_heuristics.hpp
• cpp/src/dual_simplex/branch_and_bound.cpp
• cpp/src/dual_simplex/branch_and_bound.hpp
• cpp/src/dual_simplex/diving_heuristics.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Validate algorithm correctness in optimization logic: simplex pivots, branch-and-bound decisions, routing heuristics, and constraint/objective handling must produce correct results

Applied to files:

• cpp/src/dual_simplex/simplex_solver_settings.hpp
• cpp/src/mip/diversity/lns/rins.cu
• cpp/src/dual_simplex/pseudo_costs.cpp
• cpp/src/dual_simplex/node_queue.hpp
• cpp/src/dual_simplex/diving_heuristics.hpp
• cpp/src/dual_simplex/branch_and_bound.cpp
• cpp/src/dual_simplex/pseudo_costs.hpp
• cpp/src/dual_simplex/branch_and_bound.hpp
• cpp/src/dual_simplex/diving_heuristics.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Refactor code duplication in solver components (3+ occurrences) into shared utilities; for GPU kernels, use templated device functions to avoid duplication

Applied to files:

• cpp/src/dual_simplex/simplex_solver_settings.hpp
• cpp/src/dual_simplex/pseudo_costs.cpp
• cpp/src/dual_simplex/node_queue.hpp
• cpp/src/dual_simplex/diving_heuristics.hpp
• cpp/src/dual_simplex/branch_and_bound.cpp
• cpp/src/dual_simplex/pseudo_costs.hpp
• cpp/src/dual_simplex/branch_and_bound.hpp
• cpp/src/dual_simplex/diving_heuristics.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*test*.{cpp,cu,py} : Add tests for algorithm phase transitions: verify correct initialization of bounds and state when transitioning from presolve to simplex to diving to crossover

Applied to files:

• cpp/src/dual_simplex/simplex_solver_settings.hpp
• cpp/src/dual_simplex/pseudo_costs.cpp
• cpp/src/dual_simplex/diving_heuristics.hpp
• cpp/src/dual_simplex/branch_and_bound.cpp
• cpp/src/dual_simplex/branch_and_bound.hpp
• cpp/src/dual_simplex/diving_heuristics.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Verify correct problem size checks before expensive GPU/CPU operations; prevent resource exhaustion on oversized problems

Applied to files:

• cpp/src/dual_simplex/simplex_solver_settings.hpp
• cpp/src/mip/diversity/lns/rins.cu
• cpp/src/dual_simplex/pseudo_costs.cpp
• cpp/src/dual_simplex/branch_and_bound.cpp
• cpp/src/dual_simplex/pseudo_costs.hpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Check that hard-coded GPU device IDs and resource limits are made configurable; abstract multi-backend support for different CUDA versions

Applied to files:

• cpp/src/dual_simplex/simplex_solver_settings.hpp
• cpp/src/mip/diversity/lns/rins.cu
• cpp/src/dual_simplex/pseudo_costs.cpp
• cpp/src/dual_simplex/pseudo_costs.hpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Track GPU device memory allocations and deallocations to prevent memory leaks; ensure cudaMalloc/cudaFree balance and cleanup of streams/events

Applied to files:

• cpp/src/dual_simplex/simplex_solver_settings.hpp
• cpp/src/dual_simplex/pseudo_costs.cpp
• cpp/src/dual_simplex/pseudo_costs.hpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Ensure race conditions are absent in multi-GPU code and multi-threaded server implementations; verify proper synchronization of shared state

Applied to files:

• cpp/src/dual_simplex/simplex_solver_settings.hpp
• cpp/src/mip/diversity/lns/rins.cu
• cpp/src/dual_simplex/pseudo_costs.cpp
• cpp/src/dual_simplex/node_queue.hpp
• cpp/src/dual_simplex/branch_and_bound.cpp
• cpp/src/dual_simplex/pseudo_costs.hpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cpp,hpp,h} : Avoid inappropriate use of exceptions in performance-critical GPU operation paths; prefer error codes or CUDA error checking for latency-sensitive code

Applied to files:

• cpp/src/dual_simplex/simplex_solver_settings.hpp
• cpp/src/mip/diversity/lns/rins.cu
• cpp/src/dual_simplex/pseudo_costs.cpp
• cpp/src/dual_simplex/branch_and_bound.cpp
• cpp/src/dual_simplex/pseudo_costs.hpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Verify error propagation from CUDA to user-facing APIs is complete; ensure CUDA errors are caught and mapped to meaningful user error codes

Applied to files:

• cpp/src/dual_simplex/simplex_solver_settings.hpp
• cpp/src/dual_simplex/pseudo_costs.cpp
• cpp/src/dual_simplex/branch_and_bound.cpp
• cpp/src/dual_simplex/pseudo_costs.hpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.cu : Verify race conditions and correctness of GPU kernel shared memory, atomics, and warp-level operations

Applied to files:

• cpp/src/dual_simplex/simplex_solver_settings.hpp
• cpp/src/mip/diversity/lns/rins.cu
• cpp/src/dual_simplex/pseudo_costs.cpp
• cpp/src/dual_simplex/branch_and_bound.cpp
• cpp/src/dual_simplex/pseudo_costs.hpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Eliminate unnecessary host-device synchronization (cudaDeviceSynchronize) in hot paths that blocks GPU pipeline; use streams and events for async execution

Applied to files:

• cpp/src/dual_simplex/simplex_solver_settings.hpp
• cpp/src/mip/diversity/lns/rins.cu
• cpp/src/dual_simplex/pseudo_costs.cpp
• cpp/src/dual_simplex/pseudo_costs.hpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : For concurrent CUDA operations (barriers, async operations), explicitly create and manage dedicated streams instead of reusing the default stream; document stream lifecycle

Applied to files:

• cpp/src/dual_simplex/simplex_solver_settings.hpp
• cpp/src/mip/diversity/lns/rins.cu

Learnt from: chris-maes
Repo: NVIDIA/cuopt PR: 602
File: cpp/src/linear_programming/solve.cu:732-742
Timestamp: 2025-12-04T20:09:09.264Z
Learning: In cpp/src/linear_programming/solve.cu, the barrier solver does not currently return INFEASIBLE or UNBOUNDED status. It only returns OPTIMAL, TIME_LIMIT, NUMERICAL_ISSUES, or CONCURRENT_LIMIT.

Applied to files:

• cpp/src/dual_simplex/simplex_solver_settings.hpp
• cpp/src/dual_simplex/node_queue.hpp
• cpp/src/dual_simplex/diving_heuristics.hpp
• cpp/src/dual_simplex/branch_and_bound.cpp
• cpp/src/dual_simplex/branch_and_bound.hpp
• cpp/src/dual_simplex/diving_heuristics.cpp

Learnt from: chris-maes
Repo: NVIDIA/cuopt PR: 500
File: cpp/src/dual_simplex/scaling.cpp:68-76
Timestamp: 2025-12-04T04:11:12.640Z
Learning: In the cuOPT dual simplex solver, CSR/CSC matrices (including the quadratic objective matrix Q) are required to have valid dimensions and indices by construction. Runtime bounds checking in performance-critical paths like matrix scaling is avoided to prevent slowdowns. Validation is performed via debug-only check_matrix() calls wrapped in `#ifdef` CHECK_MATRIX.

Applied to files:

• cpp/src/dual_simplex/simplex_solver_settings.hpp
• cpp/src/dual_simplex/branch_and_bound.cpp
• cpp/src/dual_simplex/branch_and_bound.hpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Reduce tight coupling between solver components (presolve, simplex, basis, barrier); increase modularity and reusability of optimization algorithms

Applied to files:

• cpp/src/dual_simplex/simplex_solver_settings.hpp
• cpp/src/dual_simplex/branch_and_bound.cpp
• cpp/src/dual_simplex/branch_and_bound.hpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cpp,hpp,h} : Prevent thread-unsafe use of global and static variables; use proper mutex/synchronization in server code accessing shared solver state

Applied to files:

• cpp/src/mip/diversity/lns/rins.cu
• cpp/src/dual_simplex/pseudo_costs.cpp
• cpp/src/dual_simplex/node_queue.hpp
• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Ensure variables and constraints are accessed from the correct problem context (original vs presolve vs folded vs postsolve); verify index mapping consistency across problem transformations

Applied to files:

• cpp/src/mip/diversity/lns/rins.cu
• cpp/src/dual_simplex/pseudo_costs.cpp
• cpp/src/dual_simplex/node_queue.hpp
• cpp/src/dual_simplex/diving_heuristics.hpp
• cpp/src/dual_simplex/branch_and_bound.cpp
• cpp/src/dual_simplex/branch_and_bound.hpp
• cpp/src/dual_simplex/diving_heuristics.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Identify assertions with overly strict numerical tolerances that fail on legitimate degenerate/edge cases (near-zero pivots, singular matrices, empty problems)

Applied to files:

• cpp/src/dual_simplex/pseudo_costs.cpp
• cpp/src/dual_simplex/branch_and_bound.cpp
• cpp/src/dual_simplex/diving_heuristics.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Assess algorithmic complexity for large-scale problems (millions of variables/constraints); ensure O(n log n) or better complexity, not O(n²) or worse

Applied to files:

• cpp/src/dual_simplex/pseudo_costs.cpp
• cpp/src/dual_simplex/diving_heuristics.hpp
• cpp/src/dual_simplex/branch_and_bound.cpp
• cpp/src/dual_simplex/diving_heuristics.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*test*.{cpp,cu,py} : Ensure test isolation: prevent GPU state, cached memory, and global variables from leaking between test cases; verify each test independently initializes its environment

Applied to files:

• cpp/src/dual_simplex/pseudo_costs.cpp
• cpp/src/dual_simplex/pseudo_costs.hpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*test*.{cpp,cu,py} : Test with free variables, singleton problems, and extreme problem dimensions near resource limits to validate edge case handling

Applied to files:

• cpp/src/dual_simplex/node_queue.hpp
• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh} : Avoid reinventing functionality already available in Thrust, CCCL, or RMM libraries; prefer standard library utilities over custom implementations

Applied to files:

• cpp/src/dual_simplex/diving_heuristics.hpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Check numerical stability: prevent overflow/underflow, precision loss, division by zero/near-zero, and use epsilon comparisons for floating-point equality checks

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp
• cpp/src/dual_simplex/diving_heuristics.cpp

Learnt from: chris-maes
Repo: NVIDIA/cuopt PR: 746
File: cpp/src/dual_simplex/barrier.cu:549-552
Timestamp: 2026-01-14T00:38:33.700Z
Learning: In cpp/src/dual_simplex/barrier.cu's form_adat() method within the barrier solver, the raft::copy from d_original_A_values to device_AD.x is necessary and must not be removed. This copy restores the original matrix A values before they are scaled by the diagonal matrix D (via d_inv_diag_prime). Since D changes between iterations and the scaling mutates device_AD.x, copying the original values each iteration is required for correctness.

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.hpp

Learnt from: aliceb-nv
Repo: NVIDIA/cuopt PR: 527
File: cpp/src/mip/diversity/lns/rins.cu:167-175
Timestamp: 2025-10-22T14:25:22.899Z
Learning: In MIP (Mixed Integer Programming) problems in the cuOPT codebase, `n_integer_vars == 0` is impossible by definition—MIP problems must have at least one integer variable. If there are no integer variables, it would be a pure Linear Programming (LP) problem, not a MIP problem.

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.hpp

cpp/src/dual_simplex/pseudo_costs.hpp (4)

• fractional (46-49)
• fractional (51-53)
• fractional (55-56)
• num_initialized_down (41-44)

cpp/src/dual_simplex/branch_and_bound.hpp (6)

• symbol (207-207)
• obj (206-206)
• solution (116-116)
• solution (134-134)
• solution (210-210)
• node (224-224)

cpp/src/dual_simplex/diving_heuristics.hpp (3)

• line_search_diving (24-27)
• pseudocost_diving (30-34)
• guided_diving (37-41)

cpp/src/dual_simplex/node_queue.hpp (4)

• node (28-32)
• node (28-28)
• node (34-38)
• node (34-34)

cpp/src/dual_simplex/node_queue.hpp (4)

• node (28-32)
• node (28-28)
• node (34-38)
• node (34-34)

cpp/src/dual_simplex/pseudo_costs.hpp (4)

• fractional (46-49)
• fractional (51-53)
• fractional (55-56)
• num_initialized_down (41-44)

[error] 8-8: 'algorithm' file not found

(clang-diagnostic-error)

[error] 10-10: 'dual_simplex/basis_updates.hpp' file not found

(clang-diagnostic-error)

[error] 10-10: 'dual_simplex/diving_heuristics.hpp' file not found

(clang-diagnostic-error)

[error] 8-8: 'dual_simplex/diving_heuristics.hpp' file not found

(clang-diagnostic-error)

📄 CodeRabbit inference engine (.github/.coderabbit_review_guide.md)

**/*.{cu,cuh,cpp,hpp,h}: Track GPU device memory allocations and deallocations to prevent memory leaks; ensure cudaMalloc/cudaFree balance and cleanup of streams/events
Validate algorithm correctness in optimization logic: simplex pivots, branch-and-bound decisions, routing heuristics, and constraint/objective handling must produce correct results
Check numerical stability: prevent overflow/underflow, precision loss, division by zero/near-zero, and use epsilon comparisons for floating-point equality checks
Validate correct initialization of variable bounds, constraint coefficients, and algorithm state before solving; ensure reset when transitioning between algorithm phases (presolve, simplex, diving, crossover)
Ensure variables and constraints are accessed from the correct problem context (original vs presolve vs folded vs postsolve); verify index mapping consistency across problem transformations
For concurrent CUDA operations (barriers, async operations), explicitly create and manage dedicated streams instead of reusing the default stream; document stream lifecycle
Eliminate unnecessary host-device synchronization (cudaDeviceSynchronize) in hot paths that blocks GPU pipeline; use streams and events for async execution
Assess algorithmic complexity for large-scale problems (millions of variables/constraints); ensure O(n log n) or better complexity, not O(n²) or worse
Verify correct problem size checks before expensive GPU/CPU operations; prevent resource exhaustion on oversized problems
Identify assertions with overly strict numerical tolerances that fail on legitimate degenerate/edge cases (near-zero pivots, singular matrices, empty problems)
Ensure race conditions are absent in multi-GPU code and multi-threaded server implementations; verify proper synchronization of shared state
Refactor code duplication in solver components (3+ occurrences) into shared utilities; for GPU kernels, use templated device functions to avoid duplication
Check that hard-coded GPU de...

Files:

• cpp/src/dual_simplex/branch_and_bound.cpp

📄 CodeRabbit inference engine (.github/.coderabbit_review_guide.md)

**/*.{cpp,hpp,h}: Check for unclosed file handles when reading MPS/QPS problem files; ensure RAII patterns or proper cleanup in exception paths
Validate input sanitization to prevent buffer overflows and resource exhaustion attacks; avoid unsafe deserialization of problem files
Prevent thread-unsafe use of global and static variables; use proper mutex/synchronization in server code accessing shared solver state

Files:

• cpp/src/dual_simplex/branch_and_bound.cpp

📄 CodeRabbit inference engine (.github/.coderabbit_review_guide.md)

Avoid inappropriate use of exceptions in performance-critical GPU operation paths; prefer error codes or CUDA error checking for latency-sensitive code

Files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Validate algorithm correctness in optimization logic: simplex pivots, branch-and-bound decisions, routing heuristics, and constraint/objective handling must produce correct results

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Validate correct initialization of variable bounds, constraint coefficients, and algorithm state before solving; ensure reset when transitioning between algorithm phases (presolve, simplex, diving, crossover)

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Ensure variables and constraints are accessed from the correct problem context (original vs presolve vs folded vs postsolve); verify index mapping consistency across problem transformations

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Verify correct problem size checks before expensive GPU/CPU operations; prevent resource exhaustion on oversized problems

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Identify assertions with overly strict numerical tolerances that fail on legitimate degenerate/edge cases (near-zero pivots, singular matrices, empty problems)

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*test*.{cpp,cu,py} : Test with free variables, singleton problems, and extreme problem dimensions near resource limits to validate edge case handling

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cpp,hpp,h} : Avoid inappropriate use of exceptions in performance-critical GPU operation paths; prefer error codes or CUDA error checking for latency-sensitive code

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Verify error propagation from CUDA to user-facing APIs is complete; ensure CUDA errors are caught and mapped to meaningful user error codes

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Check numerical stability: prevent overflow/underflow, precision loss, division by zero/near-zero, and use epsilon comparisons for floating-point equality checks

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cpp,hpp,h} : Prevent thread-unsafe use of global and static variables; use proper mutex/synchronization in server code accessing shared solver state

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Ensure race conditions are absent in multi-GPU code and multi-threaded server implementations; verify proper synchronization of shared state

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.cu : Verify race conditions and correctness of GPU kernel shared memory, atomics, and warp-level operations

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Reduce tight coupling between solver components (presolve, simplex, basis, barrier); increase modularity and reusability of optimization algorithms

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*test*.{cpp,cu,py} : Add tests for algorithm phase transitions: verify correct initialization of bounds and state when transitioning from presolve to simplex to diving to crossover

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Assess algorithmic complexity for large-scale problems (millions of variables/constraints); ensure O(n log n) or better complexity, not O(n²) or worse

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: chris-maes
Repo: NVIDIA/cuopt PR: 602
File: cpp/src/linear_programming/solve.cu:732-742
Timestamp: 2025-12-04T20:09:09.264Z
Learning: In cpp/src/linear_programming/solve.cu, the barrier solver does not currently return INFEASIBLE or UNBOUNDED status. It only returns OPTIMAL, TIME_LIMIT, NUMERICAL_ISSUES, or CONCURRENT_LIMIT.

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Refactor code duplication in solver components (3+ occurrences) into shared utilities; for GPU kernels, use templated device functions to avoid duplication

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: chris-maes
Repo: NVIDIA/cuopt PR: 500
File: cpp/src/dual_simplex/scaling.cpp:68-76
Timestamp: 2025-12-04T04:11:12.640Z
Learning: In the cuOPT dual simplex solver, CSR/CSC matrices (including the quadratic objective matrix Q) are required to have valid dimensions and indices by construction. Runtime bounds checking in performance-critical paths like matrix scaling is avoided to prevent slowdowns. Validation is performed via debug-only check_matrix() calls wrapped in `#ifdef` CHECK_MATRIX.

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

cpp/src/dual_simplex/branch_and_bound.hpp (12)

• symbol (207-207)
• obj (206-206)
• node_ptr (258-270)
• node_ptr (273-276)
• solution (116-116)
• solution (134-134)
• solution (210-210)
• node (224-224)
• task_id (229-235)
• task_id (239-239)
• start_node (243-251)
• diving_type (255-255)

cpp/src/dual_simplex/diving_heuristics.hpp (5)

• coefficient_diving (51-56)
• line_search_diving (24-27)
• pseudocost_diving (30-34)
• guided_diving (37-41)
• calculate_variable_locks (46-48)

📄 CodeRabbit inference engine (.github/.coderabbit_review_guide.md)

**/*.{cu,cuh,cpp,hpp,h}: Track GPU device memory allocations and deallocations to prevent memory leaks; ensure cudaMalloc/cudaFree balance and cleanup of streams/events
Validate algorithm correctness in optimization logic: simplex pivots, branch-and-bound decisions, routing heuristics, and constraint/objective handling must produce correct results
Check numerical stability: prevent overflow/underflow, precision loss, division by zero/near-zero, and use epsilon comparisons for floating-point equality checks
Validate correct initialization of variable bounds, constraint coefficients, and algorithm state before solving; ensure reset when transitioning between algorithm phases (presolve, simplex, diving, crossover)
Ensure variables and constraints are accessed from the correct problem context (original vs presolve vs folded vs postsolve); verify index mapping consistency across problem transformations
For concurrent CUDA operations (barriers, async operations), explicitly create and manage dedicated streams instead of reusing the default stream; document stream lifecycle
Eliminate unnecessary host-device synchronization (cudaDeviceSynchronize) in hot paths that blocks GPU pipeline; use streams and events for async execution
Assess algorithmic complexity for large-scale problems (millions of variables/constraints); ensure O(n log n) or better complexity, not O(n²) or worse
Verify correct problem size checks before expensive GPU/CPU operations; prevent resource exhaustion on oversized problems
Identify assertions with overly strict numerical tolerances that fail on legitimate degenerate/edge cases (near-zero pivots, singular matrices, empty problems)
Ensure race conditions are absent in multi-GPU code and multi-threaded server implementations; verify proper synchronization of shared state
Refactor code duplication in solver components (3+ occurrences) into shared utilities; for GPU kernels, use templated device functions to avoid duplication
Check that hard-coded GPU de...

Files:

• cpp/src/dual_simplex/branch_and_bound.cpp

📄 CodeRabbit inference engine (.github/.coderabbit_review_guide.md)

**/*.{cpp,hpp,h}: Check for unclosed file handles when reading MPS/QPS problem files; ensure RAII patterns or proper cleanup in exception paths
Validate input sanitization to prevent buffer overflows and resource exhaustion attacks; avoid unsafe deserialization of problem files
Prevent thread-unsafe use of global and static variables; use proper mutex/synchronization in server code accessing shared solver state

Files:

• cpp/src/dual_simplex/branch_and_bound.cpp

📄 CodeRabbit inference engine (.github/.coderabbit_review_guide.md)

Avoid inappropriate use of exceptions in performance-critical GPU operation paths; prefer error codes or CUDA error checking for latency-sensitive code

Files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Validate algorithm correctness in optimization logic: simplex pivots, branch-and-bound decisions, routing heuristics, and constraint/objective handling must produce correct results

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Validate correct initialization of variable bounds, constraint coefficients, and algorithm state before solving; ensure reset when transitioning between algorithm phases (presolve, simplex, diving, crossover)

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Ensure variables and constraints are accessed from the correct problem context (original vs presolve vs folded vs postsolve); verify index mapping consistency across problem transformations

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*test*.{cpp,cu,py} : Add tests for algorithm phase transitions: verify correct initialization of bounds and state when transitioning from presolve to simplex to diving to crossover

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Refactor code duplication in solver components (3+ occurrences) into shared utilities; for GPU kernels, use templated device functions to avoid duplication

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Reduce tight coupling between solver components (presolve, simplex, basis, barrier); increase modularity and reusability of optimization algorithms

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Assess algorithmic complexity for large-scale problems (millions of variables/constraints); ensure O(n log n) or better complexity, not O(n²) or worse

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Verify correct problem size checks before expensive GPU/CPU operations; prevent resource exhaustion on oversized problems

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Identify assertions with overly strict numerical tolerances that fail on legitimate degenerate/edge cases (near-zero pivots, singular matrices, empty problems)

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*test*.{cpp,cu,py} : Test with free variables, singleton problems, and extreme problem dimensions near resource limits to validate edge case handling

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cpp,hpp,h} : Avoid inappropriate use of exceptions in performance-critical GPU operation paths; prefer error codes or CUDA error checking for latency-sensitive code

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Verify error propagation from CUDA to user-facing APIs is complete; ensure CUDA errors are caught and mapped to meaningful user error codes

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Check numerical stability: prevent overflow/underflow, precision loss, division by zero/near-zero, and use epsilon comparisons for floating-point equality checks

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cpp,hpp,h} : Prevent thread-unsafe use of global and static variables; use proper mutex/synchronization in server code accessing shared solver state

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Ensure race conditions are absent in multi-GPU code and multi-threaded server implementations; verify proper synchronization of shared state

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.cu : Verify race conditions and correctness of GPU kernel shared memory, atomics, and warp-level operations

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*test*.{cpp,cu,py} : Write tests validating numerical correctness of optimization results (not just 'runs without error'); test degenerate cases (infeasible, unbounded, empty, singleton problems)

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: chris-maes
Repo: NVIDIA/cuopt PR: 500
File: cpp/src/dual_simplex/scaling.cpp:68-76
Timestamp: 2025-12-04T04:11:12.640Z
Learning: In the cuOPT dual simplex solver, CSR/CSC matrices (including the quadratic objective matrix Q) are required to have valid dimensions and indices by construction. Runtime bounds checking in performance-critical paths like matrix scaling is avoided to prevent slowdowns. Validation is performed via debug-only check_matrix() calls wrapped in `#ifdef` CHECK_MATRIX.

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: chris-maes
Repo: NVIDIA/cuopt PR: 602
File: cpp/src/linear_programming/solve.cu:732-742
Timestamp: 2025-12-04T20:09:09.264Z
Learning: In cpp/src/linear_programming/solve.cu, the barrier solver does not currently return INFEASIBLE or UNBOUNDED status. It only returns OPTIMAL, TIME_LIMIT, NUMERICAL_ISSUES, or CONCURRENT_LIMIT.

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

📄 CodeRabbit inference engine (.github/.coderabbit_review_guide.md)

**/*.{cu,cuh,cpp,hpp,h}: Track GPU device memory allocations and deallocations to prevent memory leaks; ensure cudaMalloc/cudaFree balance and cleanup of streams/events
Validate algorithm correctness in optimization logic: simplex pivots, branch-and-bound decisions, routing heuristics, and constraint/objective handling must produce correct results
Check numerical stability: prevent overflow/underflow, precision loss, division by zero/near-zero, and use epsilon comparisons for floating-point equality checks
Validate correct initialization of variable bounds, constraint coefficients, and algorithm state before solving; ensure reset when transitioning between algorithm phases (presolve, simplex, diving, crossover)
Ensure variables and constraints are accessed from the correct problem context (original vs presolve vs folded vs postsolve); verify index mapping consistency across problem transformations
For concurrent CUDA operations (barriers, async operations), explicitly create and manage dedicated streams instead of reusing the default stream; document stream lifecycle
Eliminate unnecessary host-device synchronization (cudaDeviceSynchronize) in hot paths that blocks GPU pipeline; use streams and events for async execution
Assess algorithmic complexity for large-scale problems (millions of variables/constraints); ensure O(n log n) or better complexity, not O(n²) or worse
Verify correct problem size checks before expensive GPU/CPU operations; prevent resource exhaustion on oversized problems
Identify assertions with overly strict numerical tolerances that fail on legitimate degenerate/edge cases (near-zero pivots, singular matrices, empty problems)
Ensure race conditions are absent in multi-GPU code and multi-threaded server implementations; verify proper synchronization of shared state
Refactor code duplication in solver components (3+ occurrences) into shared utilities; for GPU kernels, use templated device functions to avoid duplication
Check that hard-coded GPU de...

Files:

• cpp/src/dual_simplex/pseudo_costs.cpp
• cpp/src/mip/diversity/recombiners/sub_mip.cuh
• cpp/src/utilities/omp_helpers.hpp
• cpp/src/mip/diversity/lns/rins.cu
• cpp/src/dual_simplex/diving_heuristics.cpp
• cpp/src/dual_simplex/node_queue.hpp
• cpp/src/dual_simplex/simplex_solver_settings.hpp
• cpp/src/dual_simplex/branch_and_bound.hpp
• cpp/src/dual_simplex/branch_and_bound.cpp

📄 CodeRabbit inference engine (.github/.coderabbit_review_guide.md)

**/*.{cpp,hpp,h}: Check for unclosed file handles when reading MPS/QPS problem files; ensure RAII patterns or proper cleanup in exception paths
Validate input sanitization to prevent buffer overflows and resource exhaustion attacks; avoid unsafe deserialization of problem files
Prevent thread-unsafe use of global and static variables; use proper mutex/synchronization in server code accessing shared solver state

Files:

• cpp/src/dual_simplex/pseudo_costs.cpp
• cpp/src/utilities/omp_helpers.hpp
• cpp/src/dual_simplex/diving_heuristics.cpp
• cpp/src/dual_simplex/node_queue.hpp
• cpp/src/dual_simplex/simplex_solver_settings.hpp
• cpp/src/dual_simplex/branch_and_bound.hpp
• cpp/src/dual_simplex/branch_and_bound.cpp

📄 CodeRabbit inference engine (.github/.coderabbit_review_guide.md)

Avoid inappropriate use of exceptions in performance-critical GPU operation paths; prefer error codes or CUDA error checking for latency-sensitive code

Files:

• cpp/src/dual_simplex/pseudo_costs.cpp
• cpp/src/utilities/omp_helpers.hpp
• cpp/src/mip/diversity/lns/rins.cu
• cpp/src/dual_simplex/diving_heuristics.cpp
• cpp/src/dual_simplex/node_queue.hpp
• cpp/src/dual_simplex/simplex_solver_settings.hpp
• cpp/src/dual_simplex/branch_and_bound.hpp
• cpp/src/dual_simplex/branch_and_bound.cpp

📄 CodeRabbit inference engine (.github/.coderabbit_review_guide.md)

**/*.{cu,cuh}: Every CUDA kernel launch and memory operation must have error checking with CUDA_CHECK or equivalent verification
Avoid reinventing functionality already available in Thrust, CCCL, or RMM libraries; prefer standard library utilities over custom implementations

Files:

• cpp/src/mip/diversity/recombiners/sub_mip.cuh
• cpp/src/mip/diversity/lns/rins.cu

📄 CodeRabbit inference engine (.github/.coderabbit_review_guide.md)

Verify C API does not break ABI stability (no struct layout changes, field reordering); maintain backward compatibility in Python and server APIs with deprecation warnings

Files:

• cpp/src/utilities/omp_helpers.hpp
• cpp/src/dual_simplex/node_queue.hpp
• cpp/src/dual_simplex/simplex_solver_settings.hpp
• cpp/src/dual_simplex/branch_and_bound.hpp

📄 CodeRabbit inference engine (.github/.coderabbit_review_guide.md)

**/*.cu: Verify race conditions and correctness of GPU kernel shared memory, atomics, and warp-level operations
Detect inefficient GPU kernel launches with low occupancy or poor memory access patterns; optimize for coalesced memory access and minimize warp divergence in hot paths

Files:

• cpp/src/mip/diversity/lns/rins.cu

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Validate algorithm correctness in optimization logic: simplex pivots, branch-and-bound decisions, routing heuristics, and constraint/objective handling must produce correct results

Applied to files:

• cpp/src/dual_simplex/pseudo_costs.cpp
• cpp/src/mip/diversity/lns/rins.cu
• cpp/src/dual_simplex/diving_heuristics.cpp
• cpp/src/dual_simplex/node_queue.hpp
• cpp/src/dual_simplex/simplex_solver_settings.hpp
• cpp/src/dual_simplex/branch_and_bound.hpp
• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: chris-maes
Repo: NVIDIA/cuopt PR: 697
File: cpp/src/dual_simplex/diving_heuristics.cpp:200-228
Timestamp: 2026-01-15T20:41:51.616Z
Learning: In cpp/src/dual_simplex/diving_heuristics.cpp, the calculate_variable_locks function incorrectly indexes lp_problem.lower[nz_row] and lp_problem.upper[nz_row] where nz_row is a row index (0 to num_rows-1), but lower and upper are variable bounds of size num_cols indexed by column. This causes semantic errors and potential out-of-bounds access when num_rows > num_cols. Since lp_problem_t constraints are always equalities (A*x = rhs) after presolve, lock counting should treat each nonzero as contributing equally to both up_lock and down_lock, rather than checking constraint bounds.

Applied to files:

• cpp/src/dual_simplex/pseudo_costs.cpp
• cpp/src/mip/diversity/lns/rins.cu
• cpp/src/dual_simplex/diving_heuristics.cpp
• cpp/src/dual_simplex/node_queue.hpp
• cpp/src/dual_simplex/simplex_solver_settings.hpp
• cpp/src/dual_simplex/branch_and_bound.hpp
• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Validate correct initialization of variable bounds, constraint coefficients, and algorithm state before solving; ensure reset when transitioning between algorithm phases (presolve, simplex, diving, crossover)

Applied to files:

• cpp/src/dual_simplex/pseudo_costs.cpp
• cpp/src/mip/diversity/lns/rins.cu
• cpp/src/dual_simplex/diving_heuristics.cpp
• cpp/src/dual_simplex/node_queue.hpp
• cpp/src/dual_simplex/simplex_solver_settings.hpp
• cpp/src/dual_simplex/branch_and_bound.hpp
• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Ensure variables and constraints are accessed from the correct problem context (original vs presolve vs folded vs postsolve); verify index mapping consistency across problem transformations

Applied to files:

• cpp/src/dual_simplex/pseudo_costs.cpp
• cpp/src/mip/diversity/lns/rins.cu
• cpp/src/dual_simplex/diving_heuristics.cpp
• cpp/src/dual_simplex/node_queue.hpp
• cpp/src/dual_simplex/branch_and_bound.hpp
• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cpp,hpp,h} : Prevent thread-unsafe use of global and static variables; use proper mutex/synchronization in server code accessing shared solver state

Applied to files:

• cpp/src/dual_simplex/pseudo_costs.cpp
• cpp/src/mip/diversity/lns/rins.cu
• cpp/src/dual_simplex/node_queue.hpp
• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*test*.{cpp,cu,py} : Add tests for algorithm phase transitions: verify correct initialization of bounds and state when transitioning from presolve to simplex to diving to crossover

Applied to files:

• cpp/src/dual_simplex/pseudo_costs.cpp
• cpp/src/dual_simplex/diving_heuristics.cpp
• cpp/src/dual_simplex/simplex_solver_settings.hpp
• cpp/src/dual_simplex/branch_and_bound.hpp
• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Identify assertions with overly strict numerical tolerances that fail on legitimate degenerate/edge cases (near-zero pivots, singular matrices, empty problems)

Applied to files:

• cpp/src/dual_simplex/pseudo_costs.cpp
• cpp/src/dual_simplex/diving_heuristics.cpp
• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Assess algorithmic complexity for large-scale problems (millions of variables/constraints); ensure O(n log n) or better complexity, not O(n²) or worse

Applied to files:

• cpp/src/dual_simplex/pseudo_costs.cpp
• cpp/src/dual_simplex/diving_heuristics.cpp
• cpp/src/dual_simplex/branch_and_bound.hpp
• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Check that hard-coded GPU device IDs and resource limits are made configurable; abstract multi-backend support for different CUDA versions

Applied to files:

• cpp/src/dual_simplex/pseudo_costs.cpp
• cpp/src/mip/diversity/recombiners/sub_mip.cuh
• cpp/src/utilities/omp_helpers.hpp
• cpp/src/dual_simplex/simplex_solver_settings.hpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Track GPU device memory allocations and deallocations to prevent memory leaks; ensure cudaMalloc/cudaFree balance and cleanup of streams/events

Applied to files:

• cpp/src/dual_simplex/pseudo_costs.cpp
• cpp/src/mip/diversity/recombiners/sub_mip.cuh
• cpp/src/utilities/omp_helpers.hpp
• cpp/src/dual_simplex/simplex_solver_settings.hpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Ensure race conditions are absent in multi-GPU code and multi-threaded server implementations; verify proper synchronization of shared state

Applied to files:

• cpp/src/dual_simplex/pseudo_costs.cpp
• cpp/src/mip/diversity/recombiners/sub_mip.cuh
• cpp/src/utilities/omp_helpers.hpp
• cpp/src/mip/diversity/lns/rins.cu
• cpp/src/dual_simplex/node_queue.hpp
• cpp/src/dual_simplex/simplex_solver_settings.hpp
• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cpp,hpp,h} : Avoid inappropriate use of exceptions in performance-critical GPU operation paths; prefer error codes or CUDA error checking for latency-sensitive code

Applied to files:

• cpp/src/dual_simplex/pseudo_costs.cpp
• cpp/src/mip/diversity/recombiners/sub_mip.cuh
• cpp/src/utilities/omp_helpers.hpp
• cpp/src/mip/diversity/lns/rins.cu
• cpp/src/dual_simplex/simplex_solver_settings.hpp
• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Verify error propagation from CUDA to user-facing APIs is complete; ensure CUDA errors are caught and mapped to meaningful user error codes

Applied to files:

• cpp/src/dual_simplex/pseudo_costs.cpp
• cpp/src/mip/diversity/recombiners/sub_mip.cuh
• cpp/src/utilities/omp_helpers.hpp
• cpp/src/dual_simplex/simplex_solver_settings.hpp
• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Refactor code duplication in solver components (3+ occurrences) into shared utilities; for GPU kernels, use templated device functions to avoid duplication

Applied to files:

• cpp/src/dual_simplex/pseudo_costs.cpp
• cpp/src/mip/diversity/recombiners/sub_mip.cuh
• cpp/src/utilities/omp_helpers.hpp
• cpp/src/dual_simplex/diving_heuristics.cpp
• cpp/src/dual_simplex/node_queue.hpp
• cpp/src/dual_simplex/simplex_solver_settings.hpp
• cpp/src/dual_simplex/branch_and_bound.hpp
• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.cu : Verify race conditions and correctness of GPU kernel shared memory, atomics, and warp-level operations

Applied to files:

• cpp/src/dual_simplex/pseudo_costs.cpp
• cpp/src/mip/diversity/recombiners/sub_mip.cuh
• cpp/src/utilities/omp_helpers.hpp
• cpp/src/mip/diversity/lns/rins.cu
• cpp/src/dual_simplex/simplex_solver_settings.hpp
• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Verify correct problem size checks before expensive GPU/CPU operations; prevent resource exhaustion on oversized problems

Applied to files:

• cpp/src/dual_simplex/pseudo_costs.cpp
• cpp/src/mip/diversity/recombiners/sub_mip.cuh
• cpp/src/utilities/omp_helpers.hpp
• cpp/src/mip/diversity/lns/rins.cu
• cpp/src/dual_simplex/diving_heuristics.cpp
• cpp/src/dual_simplex/simplex_solver_settings.hpp
• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Eliminate unnecessary host-device synchronization (cudaDeviceSynchronize) in hot paths that blocks GPU pipeline; use streams and events for async execution

Applied to files:

• cpp/src/dual_simplex/pseudo_costs.cpp
• cpp/src/mip/diversity/recombiners/sub_mip.cuh
• cpp/src/utilities/omp_helpers.hpp
• cpp/src/mip/diversity/lns/rins.cu
• cpp/src/dual_simplex/simplex_solver_settings.hpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : For concurrent CUDA operations (barriers, async operations), explicitly create and manage dedicated streams instead of reusing the default stream; document stream lifecycle

Applied to files:

• cpp/src/dual_simplex/pseudo_costs.cpp
• cpp/src/mip/diversity/recombiners/sub_mip.cuh
• cpp/src/utilities/omp_helpers.hpp
• cpp/src/mip/diversity/lns/rins.cu
• cpp/src/dual_simplex/simplex_solver_settings.hpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Check numerical stability: prevent overflow/underflow, precision loss, division by zero/near-zero, and use epsilon comparisons for floating-point equality checks

Applied to files:

• cpp/src/dual_simplex/diving_heuristics.cpp
• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*test*.{cpp,cu,py} : Test with free variables, singleton problems, and extreme problem dimensions near resource limits to validate edge case handling

Applied to files:

• cpp/src/dual_simplex/diving_heuristics.cpp
• cpp/src/dual_simplex/node_queue.hpp
• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*test*.{cpp,cu,py} : Write tests validating numerical correctness of optimization results (not just 'runs without error'); test degenerate cases (infeasible, unbounded, empty, singleton problems)

Applied to files:

• cpp/src/dual_simplex/diving_heuristics.cpp
• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: chris-maes
Repo: NVIDIA/cuopt PR: 602
File: cpp/src/linear_programming/solve.cu:732-742
Timestamp: 2025-12-04T20:09:09.264Z
Learning: In cpp/src/linear_programming/solve.cu, the barrier solver does not currently return INFEASIBLE or UNBOUNDED status. It only returns OPTIMAL, TIME_LIMIT, NUMERICAL_ISSUES, or CONCURRENT_LIMIT.

Applied to files:

• cpp/src/dual_simplex/diving_heuristics.cpp
• cpp/src/dual_simplex/simplex_solver_settings.hpp
• cpp/src/dual_simplex/branch_and_bound.hpp
• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: chris-maes
Repo: NVIDIA/cuopt PR: 500
File: cpp/src/dual_simplex/scaling.cpp:68-76
Timestamp: 2025-12-04T04:11:12.640Z
Learning: In the cuOPT dual simplex solver, CSR/CSC matrices (including the quadratic objective matrix Q) are required to have valid dimensions and indices by construction. Runtime bounds checking in performance-critical paths like matrix scaling is avoided to prevent slowdowns. Validation is performed via debug-only check_matrix() calls wrapped in `#ifdef` CHECK_MATRIX.

Applied to files:

• cpp/src/dual_simplex/simplex_solver_settings.hpp
• cpp/src/dual_simplex/branch_and_bound.hpp
• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Reduce tight coupling between solver components (presolve, simplex, basis, barrier); increase modularity and reusability of optimization algorithms

Applied to files:

• cpp/src/dual_simplex/simplex_solver_settings.hpp
• cpp/src/dual_simplex/branch_and_bound.hpp
• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: chris-maes
Repo: NVIDIA/cuopt PR: 746
File: cpp/src/dual_simplex/barrier.cu:549-552
Timestamp: 2026-01-14T00:38:38.038Z
Learning: In cpp/src/dual_simplex/barrier.cu's form_adat() method within the barrier solver, the raft::copy from d_original_A_values to device_AD.x is necessary and must not be removed. This copy restores the original matrix A values before they are scaled by the diagonal matrix D (via d_inv_diag_prime). Since D changes between iterations and the scaling mutates device_AD.x, copying the original values each iteration is required for correctness.

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.hpp

Learnt from: aliceb-nv
Repo: NVIDIA/cuopt PR: 527
File: cpp/src/mip/diversity/lns/rins.cu:167-175
Timestamp: 2025-10-22T14:25:22.899Z
Learning: In MIP (Mixed Integer Programming) problems in the cuOPT codebase, `n_integer_vars == 0` is impossible by definition—MIP problems must have at least one integer variable. If there are no integer variables, it would be a pure Linear Programming (LP) problem, not a MIP problem.

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.hpp

cpp/src/dual_simplex/pseudo_costs.hpp (4)

• fractional (46-49)
• fractional (51-53)
• fractional (55-56)
• num_initialized_down (41-44)

cpp/src/dual_simplex/branch_and_bound.hpp (3)

• solution (98-98)
• solution (115-115)
• solution (192-192)

cpp/src/mip/solver.cu (6)

• solution (64-68)
• solution (64-64)
• solution (70-75)
• solution (70-72)
• solution (77-80)
• solution (77-77)

cpp/src/dual_simplex/pseudo_costs.hpp (4)

• fractional (46-49)
• fractional (51-53)
• fractional (55-56)
• num_initialized_down (41-44)

cpp/src/dual_simplex/branch_and_bound.hpp (4)

• node (206-206)
• node_ptr (240-252)
• node_ptr (257-263)
• node_ptr (266-269)

cpp/src/dual_simplex/pseudo_costs.hpp (1)

• node_ptr (31-31)

cpp/src/dual_simplex/mip_node.hpp (2)

• node_ptr (277-283)
• node_ptr (277-277)

cpp/src/dual_simplex/node_queue.hpp (4)

• node (28-32)
• node (28-28)
• node (34-38)
• node (34-34)

[error] 8-8: 'dual_simplex/diving_heuristics.hpp' file not found

(clang-diagnostic-error)

[error] 8-8: 'algorithm' file not found

(clang-diagnostic-error)

[error] 10-10: 'dual_simplex/diving_heuristics.hpp' file not found

(clang-diagnostic-error)

📄 CodeRabbit inference engine (.github/.coderabbit_review_guide.md)

**/*.{cu,cuh,cpp,hpp,h}: Track GPU device memory allocations and deallocations to prevent memory leaks; ensure cudaMalloc/cudaFree balance and cleanup of streams/events
Validate algorithm correctness in optimization logic: simplex pivots, branch-and-bound decisions, routing heuristics, and constraint/objective handling must produce correct results
Check numerical stability: prevent overflow/underflow, precision loss, division by zero/near-zero, and use epsilon comparisons for floating-point equality checks
Validate correct initialization of variable bounds, constraint coefficients, and algorithm state before solving; ensure reset when transitioning between algorithm phases (presolve, simplex, diving, crossover)
Ensure variables and constraints are accessed from the correct problem context (original vs presolve vs folded vs postsolve); verify index mapping consistency across problem transformations
For concurrent CUDA operations (barriers, async operations), explicitly create and manage dedicated streams instead of reusing the default stream; document stream lifecycle
Eliminate unnecessary host-device synchronization (cudaDeviceSynchronize) in hot paths that blocks GPU pipeline; use streams and events for async execution
Assess algorithmic complexity for large-scale problems (millions of variables/constraints); ensure O(n log n) or better complexity, not O(n²) or worse
Verify correct problem size checks before expensive GPU/CPU operations; prevent resource exhaustion on oversized problems
Identify assertions with overly strict numerical tolerances that fail on legitimate degenerate/edge cases (near-zero pivots, singular matrices, empty problems)
Ensure race conditions are absent in multi-GPU code and multi-threaded server implementations; verify proper synchronization of shared state
Refactor code duplication in solver components (3+ occurrences) into shared utilities; for GPU kernels, use templated device functions to avoid duplication
Check that hard-coded GPU de...

Files:

• cpp/src/dual_simplex/branch_and_bound.cpp

📄 CodeRabbit inference engine (.github/.coderabbit_review_guide.md)

**/*.{cpp,hpp,h}: Check for unclosed file handles when reading MPS/QPS problem files; ensure RAII patterns or proper cleanup in exception paths
Validate input sanitization to prevent buffer overflows and resource exhaustion attacks; avoid unsafe deserialization of problem files
Prevent thread-unsafe use of global and static variables; use proper mutex/synchronization in server code accessing shared solver state

Files:

• cpp/src/dual_simplex/branch_and_bound.cpp

📄 CodeRabbit inference engine (.github/.coderabbit_review_guide.md)

Avoid inappropriate use of exceptions in performance-critical GPU operation paths; prefer error codes or CUDA error checking for latency-sensitive code

Files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Validate algorithm correctness in optimization logic: simplex pivots, branch-and-bound decisions, routing heuristics, and constraint/objective handling must produce correct results

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Validate correct initialization of variable bounds, constraint coefficients, and algorithm state before solving; ensure reset when transitioning between algorithm phases (presolve, simplex, diving, crossover)

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Ensure variables and constraints are accessed from the correct problem context (original vs presolve vs folded vs postsolve); verify index mapping consistency across problem transformations

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Reduce tight coupling between solver components (presolve, simplex, basis, barrier); increase modularity and reusability of optimization algorithms

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*test*.{cpp,cu,py} : Add tests for algorithm phase transitions: verify correct initialization of bounds and state when transitioning from presolve to simplex to diving to crossover

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Assess algorithmic complexity for large-scale problems (millions of variables/constraints); ensure O(n log n) or better complexity, not O(n²) or worse

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Refactor code duplication in solver components (3+ occurrences) into shared utilities; for GPU kernels, use templated device functions to avoid duplication

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*test*.{cpp,cu,py} : Test with free variables, singleton problems, and extreme problem dimensions near resource limits to validate edge case handling

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: chris-maes
Repo: NVIDIA/cuopt PR: 697
File: cpp/src/dual_simplex/diving_heuristics.cpp:200-228
Timestamp: 2026-01-15T20:41:51.616Z
Learning: In cpp/src/dual_simplex/diving_heuristics.cpp, the calculate_variable_locks function incorrectly indexes lp_problem.lower[nz_row] and lp_problem.upper[nz_row] where nz_row is a row index (0 to num_rows-1), but lower and upper are variable bounds of size num_cols indexed by column. This causes semantic errors and potential out-of-bounds access when num_rows > num_cols. Since lp_problem_t constraints are always equalities (A*x = rhs) after presolve, lock counting should treat each nonzero as contributing equally to both up_lock and down_lock, rather than checking constraint bounds.

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Verify correct problem size checks before expensive GPU/CPU operations; prevent resource exhaustion on oversized problems

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Identify assertions with overly strict numerical tolerances that fail on legitimate degenerate/edge cases (near-zero pivots, singular matrices, empty problems)

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cpp,hpp,h} : Avoid inappropriate use of exceptions in performance-critical GPU operation paths; prefer error codes or CUDA error checking for latency-sensitive code

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Verify error propagation from CUDA to user-facing APIs is complete; ensure CUDA errors are caught and mapped to meaningful user error codes

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Check numerical stability: prevent overflow/underflow, precision loss, division by zero/near-zero, and use epsilon comparisons for floating-point equality checks

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cpp,hpp,h} : Prevent thread-unsafe use of global and static variables; use proper mutex/synchronization in server code accessing shared solver state

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Ensure race conditions are absent in multi-GPU code and multi-threaded server implementations; verify proper synchronization of shared state

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.cu : Verify race conditions and correctness of GPU kernel shared memory, atomics, and warp-level operations

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*test*.{cpp,cu,py} : Write tests validating numerical correctness of optimization results (not just 'runs without error'); test degenerate cases (infeasible, unbounded, empty, singleton problems)

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: chris-maes
Repo: NVIDIA/cuopt PR: 500
File: cpp/src/dual_simplex/scaling.cpp:68-76
Timestamp: 2025-12-04T04:11:12.640Z
Learning: In the cuOPT dual simplex solver, CSR/CSC matrices (including the quadratic objective matrix Q) are required to have valid dimensions and indices by construction. Runtime bounds checking in performance-critical paths like matrix scaling is avoided to prevent slowdowns. Validation is performed via debug-only check_matrix() calls wrapped in `#ifdef` CHECK_MATRIX.

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

Learnt from: chris-maes
Repo: NVIDIA/cuopt PR: 602
File: cpp/src/linear_programming/solve.cu:732-742
Timestamp: 2025-12-04T20:09:09.264Z
Learning: In cpp/src/linear_programming/solve.cu, the barrier solver does not currently return INFEASIBLE or UNBOUNDED status. It only returns OPTIMAL, TIME_LIMIT, NUMERICAL_ISSUES, or CONCURRENT_LIMIT.

Applied to files:

• cpp/src/dual_simplex/branch_and_bound.cpp

cpp/src/dual_simplex/presolve.cpp (3)

• convert_user_problem (559-814)
• convert_user_problem (559-563)
• convert_user_problem (1510-1515)

cpp/src/dual_simplex/branch_and_bound.hpp (9)

• obj (188-188)
• symbol (189-189)
• solution (98-98)
• solution (115-115)
• solution (192-192)
• node_ptr (240-252)
• node_ptr (257-263)
• node_ptr (266-269)
• node (206-206)

cpp/src/dual_simplex/solve.cpp (6)

• compute_user_objective (88-93)
• compute_user_objective (88-88)
• compute_user_objective (96-100)
• compute_user_objective (96-96)
• compute_user_objective (661-662)
• compute_user_objective (664-664)

cpp/src/dual_simplex/solve.hpp (2)

• compute_user_objective (37-37)
• compute_user_objective (40-40)

cpp/src/dual_simplex/pseudo_costs.hpp (4)

• node_ptr (31-31)
• fractional (46-49)
• fractional (51-53)
• fractional (55-56)

cpp/src/dual_simplex/mip_node.hpp (8)

• node_ptr (277-283)
• node_ptr (277-277)
• log (329-337)
• log (329-332)
• log (339-354)
• log (339-344)
• node_status (173-192)
• node_status (173-173)

cpp/src/dual_simplex/diving_heuristics.hpp (5)

• coefficient_diving (51-56)
• line_search_diving (24-27)
• pseudocost_diving (30-34)
• guided_diving (37-41)
• calculate_variable_locks (46-48)

cpp/src/dual_simplex/node_queue.hpp (4)

• node (28-32)
• node (28-28)
• node (34-38)
• node (34-34)