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Author: Amel Bennaceur
Publisher: Springer
ISBN: 331996562X
Category : Computers
Languages : en
Pages : 260
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Book Description
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.
Author: Amel Bennaceur
Publisher: Springer
ISBN: 331996562X
Category : Computers
Languages : en
Pages : 260
Get Book Here
Book Description
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.
Author: Bernd-Holger Schlingloff
Publisher: Springer Nature
ISBN: 303117108X
Category : Computers
Languages : en
Pages : 373
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Book Description
This book constitutes the refereed proceedings of the 20th International Conference on Software Engineering and Formal Methods, SEFM 2022, which took place in Berlin, Germany, in September 2022. The 19 full and 3 short papers included in this book were carefully reviewed and selected from 62 submissions. They were organized in topical sections as follows: software verification; program analysis; verifier technology; formal methods for intelligent and learning systems; specification and contracts; program synthesis; temporal logic; and runtime methods.
Author: Frédéric Loulergue
Publisher: Springer Nature
ISBN: 3030793796
Category : Computers
Languages : en
Pages : 117
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Book Description
This book constitutes the proceedings of the 15th International Conference on Tests and Proofs, TAP 2021, which was held as part of Software Technologies: Applications and Foundations, STAF 2021, and took place online during June 12-25, 2021. The 6 full papers included in this volume were carefully reviewed and selected from 10 submissions. They were organized in topical sections on learning, test resource allocation and benchmarks and on testing.
Author: Sharma, Avinash Kumar
Publisher: IGI Global
ISBN:
Category : Computers
Languages : en
Pages : 375
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Book Description
The rapid evolution of software engineering demands innovative approaches to meet the growing complexity and scale of modern software systems. Traditional methods often need help to keep pace with the demands for efficiency, reliability, and scalability. Manual development, testing, and maintenance processes are time-consuming and error-prone, leading to delays and increased costs. Additionally, integrating new technologies, such as AI, ML, Federated Learning, and Large Language Models (LLM), presents unique challenges in terms of implementation and ethical considerations. Advancing Software Engineering Through AI, Federated Learning, and Large Language Models provides a compelling solution by comprehensively exploring how AI, ML, Federated Learning, and LLM intersect with software engineering. By presenting real-world case studies, practical examples, and implementation guidelines, the book ensures that readers can readily apply these concepts in their software engineering projects. Researchers, academicians, practitioners, industrialists, and students will benefit from the interdisciplinary insights provided by experts in AI, ML, software engineering, and ethics.
Author: Julia M. Badger
Publisher: Springer
ISBN: 3030206521
Category : Computers
Languages : en
Pages : 410
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Book Description
This book constitutes the proceedings of the 11th International Symposium on NASA Formal Methods, NFM 2019, held in Houston, TX, USA, in May 2019. The 20 full and 8 short papers presented in this volume were carefully reviewed and selected from 102 submissions. The papers focus on formal verification, including theorem proving, model checking, and static analysis; advances in automated theorem proving including SAT and SMT solving; use of formal methods in software and system testing; run-time verification; techniques and algorithms for scaling formal methods, such as abstraction and symbolic methods, compositional techniques, as well as parallel and/or distributed techniques; code generation from formally verified models; safety cases and system safety; formal approaches to fault tolerance; theoretical advances and empirical evaluations of formal methods techniques for safety-critical systems, including hybrid and embedded systems; formal methods in systems engineering and model-based development; correct-by-design controller synthesis; formal assurance methods to handle adaptive systems.
Author: Harish Sharma
Publisher: Springer Nature
ISBN: 9811502226
Category : Technology & Engineering
Languages : en
Pages : 623
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Book Description
This book gathers selected papers presented at the International Conference on Advancements in Computing and Management (ICACM 2019). Discussing current research in the field of artificial intelligence and machine learning, cloud computing, recent trends in security, natural language processing and machine translation, parallel and distributed algorithms, as well as pattern recognition and analysis, it is a valuable resource for academics, practitioners in industry and decision-makers.
Author: Raghavendra Rao Althar
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 311070353X
Category : Computers
Languages : en
Pages : 385
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Book Description
This book will focus on utilizing statistical modelling of the software source code, in order to resolve issues associated with the software development processes. Writing and maintaining software source code is a costly business; software developers need to constantly rely on large existing code bases. Statistical modelling identifies the patterns in software artifacts and utilize them for predicting the possible issues.
Author: Dirk Beyer
Publisher: Springer Nature
ISBN: 3030311570
Category : Computers
Languages : en
Pages : 216
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Book Description
This book constitutes the refereed proceedings of the 13th International Conference on Tests and Proofs, TAP 2019, held as part of the Third World Congress on Formal Methods 2019, Porto, Portugal, in October 2019. The 10 regular papers and 2 invited paper presented in this volume were carefully reviewed and selected from 19 submissions. The TAP conference promotes research in verification and formal methods that targets the interplay of proofs and testing: the advancement of techniques of each kind and their combination, with the ultimate goal of improving software and system dependability.
Author: Andreas Holzinger
Publisher: Springer Nature
ISBN: 3030573214
Category : Computers
Languages : en
Pages : 552
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Book Description
This book constitutes the refereed proceedings of the 4th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2020, held in Dublin, Ireland, in August 2020. The 30 revised full papers presented were carefully reviewed and selected from 140 submissions. The cross-domain integration and appraisal of different fields provides an atmosphere to foster different perspectives and opinions; it will offer a platform for novel ideas and a fresh look on the methodologies to put these ideas into business for the benefit of humanity. Due to the Corona pandemic CD-MAKE 2020 was held as a virtual event.
Author: Jyotirmoy V. Deshmukh
Publisher: Springer Nature
ISBN: 3031067738
Category : Computers
Languages : en
Pages : 848
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Book Description
This book constitutes the proceedings of the 14th International Symposium on NASA Formal Methods, NFM 2022, held in Pasadena, USA, during May 24-27, 2022. The 33 full and 6 short papers presented in this volume were carefully reviewed and selected from 118submissions. The volume also contains 6 invited papers. The papers deal with advances in formal methods, formal methods techniques, and formal methods in practice. The focus on topics such as interactive and automated theorem proving; SMT and SAT solving; model checking; use of machine learning and probabilistic reasoning in formal methods; formal methods and graphical modeling languages such as SysML or UML; usability of formal method tools and application in industry, etc.
