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The benchmark results have uncovered various compiler issues. Sometimes a given compiler failed to process unusual, but otherwise grammatically valid constructs. At other times, runtime performance was shown to be below expectations, which prompted compiler developers to revise their optimization capabilities.
It is a common pattern in software testing to send values through test functions and check for correct output. In many cases, in order to thoroughly test functionalities, one needs to test multiple sets of input/output, and writing such cases separately would cause duplicate code as most of the actions would remain the same, only differing in input/output values.
A profiler can be applied to an individual method or at the scale of a module or program, to identify performance bottlenecks by making long-running code obvious. [1] A profiler can be used to understand code from a timing point of view, with the objective of optimizing it to handle various runtime conditions [2] or various loads. [3] Profiling ...
Rather than programmer-supplied frequency information, profile-guided optimization uses the results of profiling test runs of the instrumented program to optimize the final generated code. [5] [6] [7] The compiler accesses profile data from a sample run of the program across a representative input set. The results indicate which areas of the ...
In computer science, rate-monotonic scheduling (RMS) [1] is a priority assignment algorithm used in real-time operating systems (RTOS) with a static-priority scheduling class. [2] The static priorities are assigned according to the cycle duration of the job, so a shorter cycle duration results in a higher job priority.
Google Test UI is a software tool for testing computer programs, and serves as a test runner. It employs a 'test binary', a compiled program responsible for executing tests and analyzing their results, to evaluate software functionality. It visually presents the testing progress through a progress bar and displays a list of identified issues or ...
OpenMP (Open Multi-Processing) is an application programming interface (API) that supports multi-platform shared-memory multiprocessing programming in C, C++, and Fortran, [3] on many platforms, instruction-set architectures and operating systems, including Solaris, AIX, FreeBSD, HP-UX, Linux, macOS, and Windows.
The Metacode extension to C++ (Vandevoorde 2003) [1] was an early experimental system to allow compile-time function evaluation (CTFE) and code injection as an improved syntax for C++ template metaprogramming. In earlier versions of C++, template metaprogramming is often used to compute values at compile time, such as: