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_aMachine Learning for Dynamic Software Analysis: Potentials and Limits _h[electronic resource] : _bInternational Dagstuhl Seminar 16172, Dagstuhl Castle, Germany, April 24-27, 2016, Revised Papers / _cedited by Amel Bennaceur, Reiner Hähnle, Karl Meinke. |
250 | _a1st ed. 2018. | ||
264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2018. |
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300 |
_aIX, 257 p. 38 illus. _bonline resource. |
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336 |
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490 | 1 |
_aProgramming and Software Engineering ; _v11026 |
|
500 | _aAcceso multiusuario | ||
505 | 0 | _aIntroduction -- Testing and Learning -- Extensions of Automata Learning -- Integrative Approaches. | |
520 | _aMachine learning of software artefacts is an emerging area of interaction between the machine learning and software analysis communities. Increased productivity in software engineering relies on the creation of new adaptive, scalable tools that can analyse large and continuously changing software systems. These require new software analysis techniques based on machine learning, such as learning-based software testing, invariant generation or code synthesis. Machine learning is a powerful paradigm that provides novel approaches to automating the generation of models and other essential software artifacts. This volume originates from a Dagstuhl Seminar entitled "Machine Learning for Dynamic Software Analysis: Potentials and Limits" held in April 2016. The seminar focused on fostering a spirit of collaboration in order to share insights and to expand and strengthen the cross-fertilisation between the machine learning and software analysis communities. The book provides an overview of the machine learning techniques that can be used for software analysis and presents example applications of their use. Besides an introductory chapter, the book is structured into three parts: testing and learning, extension of automata learning, and integrative approaches. | ||
541 |
_fUABC ; _cTemporal ; _d01/01/2021-12/31/2023. |
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650 | 0 | _aSoftware engineering. | |
650 | 0 | _aArtificial intelligence. | |
650 | 0 | _aComputers. | |
650 | 1 | 4 |
_aSoftware Engineering/Programming and Operating Systems. _0https://scigraph.springernature.com/ontologies/product-market-codes/I14002 |
650 | 2 | 4 |
_aArtificial Intelligence. _0https://scigraph.springernature.com/ontologies/product-market-codes/I21000 |
650 | 2 | 4 |
_aTheory of Computation. _0https://scigraph.springernature.com/ontologies/product-market-codes/I16005 |
700 | 1 |
_aBennaceur, Amel. _eeditor. _0(orcid)0000-0002-6124-9622 _1https://orcid.org/0000-0002-6124-9622 _4edt _4http://id.loc.gov/vocabulary/relators/edt |
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700 | 1 |
_aHähnle, Reiner. _eeditor. _0(orcid)0000-0001-8000-7613 _1https://orcid.org/0000-0001-8000-7613 _4edt _4http://id.loc.gov/vocabulary/relators/edt |
|
700 | 1 |
_aMeinke, Karl. _eeditor. _0(orcid)0000-0002-9706-5008 _1https://orcid.org/0000-0002-9706-5008 _4edt _4http://id.loc.gov/vocabulary/relators/edt |
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_iPrinted edition: _z9783319965611 |
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_iPrinted edition: _z9783319965635 |
830 | 0 |
_aProgramming and Software Engineering ; _v11026 |
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_zLibro electrónico _uhttp://148.231.10.114:2048/login?url=https://doi.org/10.1007/978-3-319-96562-8 |
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