$ show optimatika/ojAlgo
ojAlgo is a pure Java numerical computing library providing high-performance linear algebra (dense and sparse matrices, decompositions like LU, QR, SVD, Cholesky, eigenvalue), optimization (linear programming via simplex, convex QP via active-set/ADMM, integer programming with branch-and-cut), neural networks, statistical distributions, random processes, time series analysis, clustering, financial portfolio models, and special functions. It has zero external dependencies and is modularized via JPMS. The architecture is a classic library: users create matrix objects or optimization models, invoke solvers or decompositions, and retrieve results. Key entry points include `MatrixStore`, `ExpressionsBasedModel`, `ArtificialNeuralNetwork`, and various decomposition factories. The codebase is well-tested with extensive unit and regression tests, and demonstrates strong engineering practices such as interface-driven design, factory patterns, and careful numerical stability. While primarily a software library, it also contains data analysis and research-oriented components (clustering, financial series, random processes), making it a hybrid but dominantly an application library.
The LLM identified 5 files worth highlighting for reuse:
A time-based cache map that automatically removes entries after a configurable time-to-live. It uses a background thread to periodically evict expired entries and supports a disposer callback for cleanup. The implementation is self-contained (only depends on standard Java and the `Disposable` interface) and can be extracted into any project needing a simple, thread-safe, expiring cache.
A compact, long-backed bit set for enums with up to 64 values. Provides set operations (union, intersection, complement) and iteration over set bits. It is a standalone utility class with no internal dependencies, demonstrating efficient use of bitwise operations for enum flags.
A utility class with static methods for power-of-2 calculations: adjusting up/down to nearest power of 2, checking if a number is a power of 2, and computing integer/long powers. It uses bitwise operations for efficiency and has no dependencies, making it trivially reusable.
A framework for parallel processing of ranges using a divide-and-conquer strategy. It splits a range into segments, processes them in parallel via a configurable executor, and combines results. The class is parameterized on the worker type and supports thresholds for granularity. While it depends on internal concurrency utilities, the pattern is clean and could be extracted with minimal adaptation.
A generic, thread-safe object pool that manages reusable instances. It supports configurable pool size, factory for creating new objects, and a disposer for cleanup. The implementation uses a `LinkedBlockingQueue` and is self-contained (depends only on `Disposable`). It can be extracted for any pooling need.