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Concurrent and parallel programming languages involve multiple timelines. Such languages provide synchronization constructs whose behavior is defined by a parallel execution model. A concurrent programming language is defined as one which uses the concept of simultaneously executing processes or threads of execution as a means of structuring a ...
The Java programming language and the Java virtual machine (JVM) are designed to support concurrent programming. All execution takes place in the context of threads. Objects and resources can be accessed by many separate threads. Each thread has its own path of execution, but can potentially access any object in the program.
Declarative programming – describes what computation should perform, without specifying detailed state changes c.f. imperative programming (functional and logic programming are major subgroups of declarative programming) Distributed programming – have support for multiple autonomous computers that communicate via computer networks
Notable programming sources use terms like C-style, C-like, a dialect of C, having C-like syntax. The term curly bracket programming language denotes a language that shares C's block syntax. [1] [2] C-family languages have features like: Code block delimited by curly braces ({}), a.k.a. braces, a.k.a. curly brackets; Semicolon (;) statement ...
As a simple example, if a system is running code on a 2-processor system (CPUs "a" & "b") in a parallel environment and we wish to do tasks "A" and "B", it is possible to tell CPU "a" to do task "A" and CPU "b" to do task "B" simultaneously, thereby reducing the run time of the execution.
Many concurrent programming languages have been developed more as research languages (e.g. Pict) rather than as languages for production use. However, languages such as Erlang, Limbo, and occam have seen industrial use at various times in the last 20 years. A non-exhaustive list of languages which use or provide concurrent programming facilities:
Such programs therefore do not benefit from hardware multithreading and can indeed see degraded performance due to contention for shared resources. From the software standpoint, hardware support for multithreading is more visible to software, requiring more changes to both application programs and operating systems than multiprocessing.
In the C programming language, each thread has its own stack. However, a static variable is not kept on the stack; all threads share simultaneous access to it. If multiple threads overlap while running the same function, it is possible that a static variable might be changed by one thread while another is midway through checking it.