Название: Concurrency, Specification and Programming: Revised Selected Papers from the 29th International Workshop on Concurrency
Автор: Bernd-Holger Schlingloff, Thomas Vogel, Andrzej Skowron
Издательство: Springer
Серия: Studies in Computational Intelligence
Год: 2023
Страниц: 234
Язык: английский
Формат: pdf (true), epub
Размер: 21.9 MB

This book presents novel approaches to the formal specification of concurrent and parallel systems, mathematical models for describing such systems, and programming and verification concepts for their implementation. A special emphasis is on methods based on artificial intelligence and machine learning techniques. Chapters are revised selected papers from the 29th International Workshop on Concurrency, Specification, and Programming (CS&P 2021), Berlin, Germany. Nine independent chapters cover formal approaches to topics such as requirements formalization, parsing, or granular computing, as well as their applications in recommender systems, decision making, security, optimization, and other areas. The book thus addresses both researchers and practitioners in its field.

The program of CS&P’21 comprised two invited keynotes and presentations of 16 peer-reviewed papers. All talks reflect the current trends in the CS&P field: there are “classical” contributions on the theory of concurrency, specification and programming such as event/data-based systems, cause-effect structures, granular computing, and time Petri nets. However, more and more papers are also concerned with artificial intelligence and machine learning techniques, e.g., in the set of pairs of objects, or with sparse neural networks. Moreover, application areas such as the prediction of football game results, the classification of dry beans or the care for honeybees are the focus of attention. Furthermore, this volume contains several papers on software quality assurance, e.g., fault localization and automated testing of software-based systems.

Numerous approaches based on natural language processing (NLP) have been proposed in the literature to generate requirements models using mainly syntactic properties. Recent advances in NLP show that semantic quantities can also be identified and used to provide better assistance in the requirements formalization process. In this work, we present and discuss principal ideas and state-of-the-art methodologies from the field of NLP in order to guide the readers on how to derive new requirements formalization approaches according to their specific use case and needs. We demonstrate our approaches on two industrial use cases from the automotive and railway domains and show that the use of current pre-trained NLP models requires less effort to adapt to a specific use case. Furthermore, we outline findings and shortcomings of this research area and propose some promising future developments.

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