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Название: Machine Learning for Dynamic Software Analysis: Potentials and Limits
Автор: Amel Bennaceur
Издательство: Springer
Год: 2018
Страниц: 257
Формат: PDF, EPUB
Размер: 15 Mb
Язык: English
Machine 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.