Machine Learning for Dynamic Software Analysis: Potentials and Limits

International Dagstuhl Seminar 16172, Dagstuhl Castle, Germany, April 24-27, 2016, Revised Papers

Amel Bennaceur, Reiner Hähnle, Karl Meinke (Herausgeber)

Buch | Softcover

IX, 257 Seiten

2018
Springer International Publishing (Verlag)
978-3-319-96561-1 (ISBN)

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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. 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.

Introduction.- Testing and Learning.- Extensions of Automata Learning.- Integrative Approaches.

Erscheinungsdatum	22.07.2018
Reihe/Serie	Lecture Notes in Computer Science
Reihe/Serie	Programming and Software Engineering
Zusatzinfo	IX, 257 p. 38 illus.
Verlagsort	Cham
Sprache	englisch
Maße	155 x 235 mm
Gewicht	410 g
Themenwelt	Mathematik / Informatik ► Informatik ► Software Entwicklung
Themenwelt	Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
Schlagworte	Active learning • Applications • Artificial Intelligence • automated static analysis • Computer Science • Computing Methodologies • conference proceedings • Dynamic Analysis • formal languages and automata theory • formal methods • Informatics • machine learning • model development and analysis • Research • Semantics • Software Design • Software engineering • Specifications • Theory and algorithms for application domains • Theory of Computation
ISBN-10	3-319-96561-1 / 3319965611
ISBN-13	978-3-319-96561-1 / 9783319965611
Zustand	Neuware