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  2. Comparison of online source code playgrounds - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_online...

    Playground Access PHP Ruby/Rails Python/Django SQL Other DB Fiddle [am]: Free & Paid No No No Yes MySQL, PostgreSQL, SQLite dbfiddle [an]: Free No No No Yes Db2, Firebird, MariaDB, MySQL, Node.js, Oracle, Postgres, SQL Server, SQLite, YugabyteDB

  3. List of concurrent and parallel programming languages

    en.wikipedia.org/wiki/List_of_concurrent_and...

    In both cases, the features must be part of the language syntax and not an extension such as a library (libraries such as the posix-thread library implement a parallel execution model but lack the syntax and grammar required to be a programming language).

  4. Java concurrency - Wikipedia

    en.wikipedia.org/wiki/Java_concurrency

    The Java memory model describes how threads in the Java programming language interact through memory. On modern platforms, code is frequently not executed in the order it was written. It is reordered by the compiler, the processor and the memory subsystem to achieve maximum performance.

  5. Jump threading - Wikipedia

    en.wikipedia.org/wiki/Jump_threading

    In computing, jump threading is a compiler optimization of one jump directly to a second jump. If the second condition is a subset or inverse of the first, it can be eliminated, or threaded through the first jump. [1] This is easily done in a single pass through the program, following acyclic chained jumps until the compiler arrives at a fixed ...

  6. Speculative multithreading - Wikipedia

    en.wikipedia.org/wiki/Speculative_multithreading

    The speculative thread will need to be discarded or re-run if its presumptions on the input state prove to be invalid. It is a dynamic (runtime) parallelization technique that can uncover parallelism that static (compile-time) parallelization techniques may fail to exploit because at compile time thread independence cannot be guaranteed. For ...

  7. Automatic parallelization - Wikipedia

    en.wikipedia.org/wiki/Automatic_parallelization

    Automatic parallelization by compilers or tools is very difficult due to the following reasons: [6] dependence analysis is hard for code that uses indirect addressing, pointers, recursion, or indirect function calls because it is difficult to detect such dependencies at compile time; loops have an unknown number of iterations;

  8. Modula-3 - Wikipedia

    en.wikipedia.org/wiki/Modula-3

    Modula-3 is a programming language conceived as a successor to an upgraded version of Modula-2 known as Modula-2+.It has been influential in research circles (influencing the designs of languages such as Java, C#, Python [8] and Nim), but it has not been adopted widely in industry.

  9. Threaded code - Wikipedia

    en.wikipedia.org/wiki/Threaded_code

    Some programmers consider the "p-code" generated by some Pascal compilers, as well as the bytecodes used by .NET, Java, BASIC and some C compilers, to be token-threading. A common approach, historically, is bytecode , which typically uses 8-bit opcodes with a stack-based virtual machine.