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IPOPT can be called from various modeling environments: C, C++, Fortran, Java, R, Python, and others. [2] IPOPT is part of the COIN-OR project. IPOPT is designed to exploit 1st derivative and 2nd derivative information if provided (usually via automatic differentiation routines in modeling environments such as AMPL).
OR-Tools was created by Laurent Perron in 2011. [5]In 2014, Google's open source linear programming solver, GLOP, was released as part of OR-Tools. [1]The CP-SAT solver [6] bundled with OR-Tools has been consistently winning gold medals in the MiniZinc Challenge, [7] an international constraint programming competition.
Written in C++ and published under an MIT license, HiGHS provides programming interfaces to C, Python, Julia, Rust, R, JavaScript, Fortran, and C#. It has no external dependencies. A convenient thin wrapper to Python is available via the highspy PyPI package. Although generally single-threaded, some solver components can utilize multi-core ...
Arm MAP, a performance profiler supporting Linux platforms.; AppDynamics, an application performance management solution [buzzword] for C/C++ applications via SDK.; AQtime Pro, a performance profiler and memory allocation debugger that can be integrated into Microsoft Visual Studio, and Embarcadero RAD Studio, or can run as a stand-alone application.
The Eclipse IDE has code completion tools that come packaged with the program. [15] [16] It includes notable support for Java, C++, and JavaScript code authoring. The Code Recommenders Eclipse project used to provide powerful intelligent completion, [17] but due to lack of resources, was dropped in Eclipse 2018–12, and then archived in July 2019.
CodeLite features project management (workspace/projects), code completion, code refactoring, source browsing, syntax highlighting, Subversion integration, cscope integration, UnitTest++ integration, an interactive debugger built over gdb and a source code editor (based on Scintilla).
PyDev received improvements to type inference and a notable increase in contributions to code base when version 2.8 was released in July 2013. [6] Since then, numerous additional improvements have been made to PyDev and it has gained many positive reviews.
PMD is able to detect flaws or possible flaws in source code, like: Bugs—Empty try/catch/finally/switch blocks. Dead code—Unused local variables, parameters and private methods. Empty if/while statements. Overcomplicated expressions—Unnecessary if statements, for loops that could be while loops.