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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 ...
Dataflow programming – forced recalculation of formulas when data values change (e.g. spreadsheets) 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)
The number of threads may be dynamically adjusted during the lifetime of an application based on the number of waiting tasks. For example, a web server can add threads if numerous web page requests come in and can remove threads when those requests taper down. [disputed – discuss] The cost of having a larger thread pool is increased resource ...
For example, if the goal is to execute "push A, push B, add", the following might be used. Here, ip is initialized to address &thread , each code fragment ( push , add ) is found by double-indirecting through ip and an indirect block; and any operands to the fragment are found in the indirect block following the fragment's address.
Cooperative multitasking is similar to async/await in languages, such as JavaScript or Python, that feature a single-threaded event-loop in their runtime. This contrasts with cooperative multitasking in that await cannot be invoked from a non-async function, but only an async function, which is a kind of coroutine .
Multiple dispatch or multimethods is a feature of some programming languages in which a function or method can be dynamically dispatched based on the run-time (dynamic) type or, in the more general case, some other attribute of more than one of its arguments. [1]
Concurrent programming languages are programming languages that use language constructs for concurrency. These constructs may involve multi-threading, support for distributed computing, message passing, shared resources (including shared memory) or futures and promises.
However, this can be viewed as unneeded complexity. In programming languages based on threads, the most expressive approach seems to be to provide a mix of non-thread-specific futures, read-only views, and either a WaitNeeded construct, or support for transparent forwarding.