Month: 2025-10 | Repository: opencompl/lean-mlir. This month focused on delivering foundational features for floating-point analysis, improving code organization, and aligning planning with PLDI milestones. Key work included FP support in Medusa, documentation and planning updates, and a major refactor of the boolean structure into the Hydra library. No major bug fixes were reported in this period. - Floating-point expression support in Medusa: introduced a dedicated FP expressions module with data structures, reflection, and parsing to enable robust analysis of floating-point code. Integrated Fp.lean definitions into FpExpr.eval to ensure consistency across FP evaluation. Commits: 6aec1af634fc6dcf8835c1b256067dab8929d997; f5b373945bcff6abf2506b908e12f924d6c27560. - Documentation and planning updates: refreshed README to reflect PLDI task statuses and added planning items for algorithm improvements (e.g., bv_abstract) to guide next milestones. Commits: 40a58a40b5a4d9c3c6340c62c5defcd0e7e24b8f; 1c2b692a797c79aa2221eacba767dc4bca9634fd. - Boolean structure refactor into Hydra library: moved boolean structure into Hydra library, cleaned up typeclass instances, and switched from BEq to DecidableEq to improve properties and maintainability. Commit: 4e5d3bf293a5f15d2ec02b190f8d862d4da8f0e5. Overall impact: These changes broaden FP analysis capabilities in Medusa, improve maintainability and type-safety through library refactors, and establish a clearer PLDI-focused roadmap. The work lays groundwork for more robust FP optimization and verification in future sprints. Technologies/skills demonstrated: Lean-based FP modeling (Fp.lean), Medusa module development, Hydra library integration, typeclass modernization (DecidableEq), documentation and task planning, and disciplined commit hygiene.

September 2025 (opencompl/lean-mlir) jointly delivered Blase-focused enhancements to support multi-width decision procedures, width tracking, and CI modernization. The work increases verification depth, reduces feedback cycles, and improves developer onboarding for width-aware analysis. Key features delivered: - Blase multi-width decision procedure core with ULT support, built-out width-specific ops, and testing framework for Blase/multi-width; includes scanAnd on unary width encoded bitvectors. - Blase width support documentation: README, usage instructions, and TODO scaffolding to accelerate adoption. - Maintenance improvements: width tracking, a new width abstraction config option, and updated tests ensuring correctness across width variants. - Blase CI and evaluation workflow modernization: parallel CI runs when Blase changes, renamed CI steps, and consolidation of evaluation pipelines for faster feedback. - Blase feature enhancements: added wider width operations and predicate variable support; boolean sort support; and improvements to failure reporting. Major bugs fixed: - Fixed a misspelled Blase name in the codebase. - Fixed an example preprocessing bug related to Blase handling of ofBool. Overall impact and accomplishments: - Increased verification depth and reliability through multi-width support and broader operation coverage. - Faster feedback loops due to CI/evaluation workflow modernization and parallelization. - Improved developer onboarding and maintainability via documentation, tests, and configuration options. - Strengthened usability and debugging with enhanced failure reporting and new predicate-variable/boolean sorting support. Technologies/skills demonstrated: - Blase architecture and multi-width strategies, including ULT-based reasoning and bitvector handling. - Width tracking, abstraction/config design, and test architecture for width-variant features. - CI/CD modernization, pipeline configuration, and evaluation workflow orchestration. - Documentation, preprocessing robustness, and feature refinement for user-facing tooling.

August 2025 (opencompl/lean-mlir) delivered substantial reliability, performance, and extensibility improvements across CI, solver, testing, and project structure. Key outcomes include CI integrity checks to lock goals during runs, preventing drift and ensuring reproducible results; a multi-width solver with enhanced arithmetic and correct zext/sext semantics; expanded testing and output capabilities (sext tests, simplified extract-goals output, TacBench JSONL outputs, and sampling runs) enabling faster validation and data-driven evaluation; TacBench restructuring and instrumentation to a separate Lake project for cleaner reuse and customer deployments; extract-goals stride/offset enhancements with batch processing options (followed by a controlled revert to maintain stability); improved update-goals error handling to surface failures earlier; and SSA cleanup to reduce dependencies. Business value accrued includes more reliable CI-driven correctness, faster and richer evaluation pipelines, easier customer integration, and reduced maintenance overhead.

July 2025 performance summary for lean-mlir (opencompl/lean-mlir). Focused on maintainability, modularization, and CI/reproducibility enhancements, delivering several features and a critical bug fix. Key outcomes include repository cleanup and reorganization, extraction of goal states into separate files, Nix/Flakes-based CI migration with Docker image support, plotting variance computation, multi-width definitions with reflectability, artifact number updates, and initial FSM refactor, plus refreshed PDF assets. Fixed a path handling bug to stabilize builds and workflows. These changes reduce maintenance effort, improve reproducibility, and accelerate feature delivery while enhancing data visualization and artifact integrity.

June 2025 performance summary for lean-mlir and lean4: focused on strengthening verification, performance visibility, and tooling to accelerate safe delivery of complex formal artifacts. The work delivered improved reliability of the K-induction pipeline, expanded AIG/Empty-type support, added robust profiling, and enhanced data output and artifact management to support reproducible evaluations and customer-facing documentation.

May 2025 monthly performance summary focusing on key accomplishments across leanprover/lean4 and opencompl/lean-mlir. The month delivered targeted features to strengthen formal verification capabilities and modernize the frontend, resulting in clearer invariants handling and improved maintainability. Business value centers on enabling faster, more reliable proofs for bitvector reasoning and reducing technical debt through frontend migration.

Monthly summary for 2025-04 focusing on cross-repo feature delivery and performance-oriented improvements in Lean tooling and MLIR-assisted workflows. Delivered two targeted feature enhancers in leanprover/lean4 and opencompl/lean-mlir, with an emphasis on improving bitvector reasoning, tactic normalization, and benchmarking capabilities. Highlights include new BitVec arithmetic theorems and simprocs, plus integrated benchmarking scaffolding for bv_normalize within InstCombine, enabling data-driven optimization. Key achievements (top 3-5): - Lean4: BitVec.append_add_append_eq_append theorem and associated bv-concat-extract normalization simprocs added to streamline concatenation and addition for non-overlapping or zero-padded bitvectors, improving normalization tactics and performance. Commits: 55b0d390c6de93afd792cab0deef2d721c3a4fe8; 0f7eb710e298e99984840d5f8120762ae37dbd31. - Lean-mlir: bv_normalize tactic benchmarking integration added to InstCombine workflow, with environment setup for Python virtual environments and improved scripts for benchmarking and plotting. Commit: 32bc43bf58ffbad634077392c198d784925a81b9. - Operational groundwork: Established reproducible benchmarking pipelines and scaffolding across repos to support data-driven performance improvements in future sprints. Overall impact: Accelerated formal verification workflows by enhancing bitvector reasoning speed and reliability, and laid the groundwork for measurable performance optimization through standardized benchmarks across Lean4 and MLIR-based tooling. Technologies/skills demonstrated: Lean4 theory engineering (BitVec, simprocs, normalization), tactic design and automation, MLIR/InstCombine integration, benchmarking, Python environment management, and scripting for data-driven performance analysis.

March 2025 (2025-03) performance and verification sprint across lean-mlir and Lean4 focusing on benchmarking, formal BV reasoning, and reliability improvements. Key outcomes include a scalable MBA benchmarking and plotting framework, a BV lemmas library, tactic reliability fixes, and substantial BV theory enhancements that improve bit-blasting efficiency and proof automation.

February 2025 performance summary for opencompl/lean-mlir: Delivered core automation for automata tactics benchmarking and verification, introduced resource safeguards to prevent unbounded evaluation times, and enhanced evaluation tooling for width-generic tactics and BV circuit automata. These changes provide repeatable benchmarks, richer bitvector verification, and more stable, data-backed performance metrics to accelerate development and paper-related experiments.

January 2025 performance snapshot for opencompl/lean-mlir and lean4 development efforts. This month focused on delivering scalable formal verification capabilities, tightening reliability of the verification pipeline, and accelerating the development workflow through tooling and CI improvements.

December 2024 monthly summary focusing on key accomplishments, with emphasis on feature deliverables across leanprover/lean4 and opencompl/lean-mlir. Delivered formal theorems for bitvector unsigned right shift, extended circuit-based automata with predicates and fixed-width constraints, enhanced bitstream arithmetic (toInt, leftShift, and breakdown of multiplication), and improved circuit automata tactic robustness with better usability and metrics collection. These work collectively advance formal verification capabilities, scalable decision procedures for bitvectors, and operator support for fixed-width contexts, enabling more reliable and efficient proof tooling and compiler-like reasoning.

November 2024 monthly summary focusing on key accomplishments, business value, and technical achievements across Lean4 and lean-mlir repositories.