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  2. Exception handling (programming) - Wikipedia

    en.wikipedia.org/wiki/Exception_handling...

    Exceptions can be used to represent and handle abnormal, unpredictable, erroneous situations, but also as flow control structures to handle normal situations. For example, Python's iterators throw StopIteration exceptions to signal that there are no further items produced by the iterator. [1]

  3. Thread safety - Wikipedia

    en.wikipedia.org/wiki/Thread_safety

    Thread safety guarantees usually also include design steps to prevent or limit the risk of different forms of deadlocks, as well as optimizations to maximize concurrent performance. However, deadlock-free guarantees cannot always be given, since deadlocks can be caused by callbacks and violation of architectural layering independent of the ...

  4. List of concurrent and parallel programming languages

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

    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 ...

  5. Monitor (synchronization) - Wikipedia

    en.wikipedia.org/wiki/Monitor_(synchronization)

    In concurrent programming, a monitor is a synchronization construct that prevents threads from concurrently accessing a shared object's state and allows them to wait for the state to change. They provide a mechanism for threads to temporarily give up exclusive access in order to wait for some condition to be met, before regaining exclusive ...

  6. Embarrassingly parallel - Wikipedia

    en.wikipedia.org/wiki/Embarrassingly_parallel

    "Embarrassingly" is used here to refer to parallelization problems which are "embarrassingly easy". [4] The term may imply embarrassment on the part of developers or compilers: "Because so many important problems remain unsolved mainly due to their intrinsic computational complexity, it would be embarrassing not to develop parallel implementations of polynomial homotopy continuation methods."

  7. Concurrent data structure - Wikipedia

    en.wikipedia.org/wiki/Concurrent_data_structure

    Concurrent data structures are significantly more difficult to design and to verify as being correct than their sequential counterparts. The primary source of this additional difficulty is concurrency, exacerbated by the fact that threads must be thought of as being completely asynchronous: they are subject to operating system preemption, page faults, interrupts, and so on.

  8. Dining philosophers problem - Wikipedia

    en.wikipedia.org/wiki/Dining_philosophers_problem

    Illustration of the dining philosophers problem. Each philosopher has a bowl of spaghetti and can reach two of the forks. In computer science, the dining philosophers problem is an example problem often used in concurrent algorithm design to illustrate synchronization issues and techniques for resolving them.

  9. Structured concurrency - Wikipedia

    en.wikipedia.org/wiki/Structured_concurrency

    The fork–join model from the 1960s, embodied by multiprocessing tools like OpenMP, is an early example of a system ensuring all threads have completed before exit.. However, Smith argues that this model is not true structured concurrency as the programming language is unaware of the joining behavior, and is thus unable to enforce

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