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  2. Data-driven testing - Wikipedia

    en.wikipedia.org/wiki/Data-driven_testing

    Data-driven testing (DDT), also known as table-driven testing or parameterized testing, is a software testing methodology that is used in the testing of computer software to describe testing done using a table of conditions directly as test inputs and verifiable outputs as well as the process where test environment settings and control are not hard-coded.

  3. pytest - Wikipedia

    en.wikipedia.org/wiki/Pytest

    Functions declared as pytest fixtures are marked by the @pytest.fixture decorator, whose names can then be passed into test functions as parameters. [12] When pytest finds the fixtures' names in test functions' parameters, it first searches in the same module for such fixtures, and if not found, it searches for such fixtures in the conftest.py ...

  4. Elasticsearch - Wikipedia

    en.wikipedia.org/wiki/Elasticsearch

    Elasticsearch is a search engine based on Apache Lucene. It provides a distributed, multitenant -capable full-text search engine with an HTTP web interface and schema-free JSON documents. Official clients are available in Java , [ 2 ] .NET [ 3 ] ( C# ), PHP , [ 4 ] Python , [ 5 ] Ruby [ 6 ] and many other languages. [ 7 ]

  5. Okapi BM25 - Wikipedia

    en.wikipedia.org/wiki/Okapi_BM25

    In information retrieval, Okapi BM25 (BM is an abbreviation of best matching) is a ranking function used by search engines to estimate the relevance of documents to a given search query. It is based on the probabilistic retrieval framework developed in the 1970s and 1980s by Stephen E. Robertson , Karen Spärck Jones , and others.

  6. Full-text search - Wikipedia

    en.wikipedia.org/wiki/Full-text_search

    In text retrieval, full-text search refers to techniques for searching a single computer-stored document or a collection in a full-text database. Full-text search is distinguished from searches based on metadata or on parts of the original texts represented in databases (such as titles, abstracts, selected sections, or bibliographical references).

  7. Hyperparameter optimization - Wikipedia

    en.wikipedia.org/wiki/Hyperparameter_optimization

    In machine learning, hyperparameter optimization [1] or tuning is the problem of choosing a set of optimal hyperparameters for a learning algorithm. A hyperparameter is a parameter whose value is used to control the learning process, which must be configured before the process starts.

  8. Test automation - Wikipedia

    en.wikipedia.org/wiki/Test_automation

    Test automation tools can be expensive and are usually employed in combination with manual testing. Test automation can be made cost-effective in the long term, especially when used repeatedly in regression testing. A good candidate for test automation is a test case for common flow of an application, as it is required to be executed ...

  9. Parametric search - Wikipedia

    en.wikipedia.org/wiki/Parametric_search

    Instead, when applicable, parametric search finds strongly polynomial algorithms, whose running time is a function only of the input size and is independent of numerical precision. However, parametric search leads to an increase in time complexity (compared to the decision algorithm) that may be larger than logarithmic.

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