Mining Software Engineering Data for Software Reuse

1. Auflage 2020
ISBN: 978-3-030-30105-7
Verlag: Springer International Publishing

Buch, Englisch, 242 Seiten, HC runder Rücken kaschiert, Format (B × H): 160 mm x 241 mm, Gewicht: 565 g

Reihe: Advanced Information and Knowledge Processing

This monograph discusses software reuse and how it can be applied at different stages of the software development process, on different types of data and at different levels of granularity. Several challenging hypotheses are analyzed and confronted using novel data-driven methodologies, in order to solve problems in requirements elicitation and specification extraction, software design and implementation, as well as software quality assurance.

The book is accompanied by a number of tools, libraries and working prototypes in order to practically illustrate how the phases of the software engineering life cycle can benefit from unlocking the potential of data.

Software engineering researchers, experts, and practitioners can benefit from the various methodologies presented and can better understand how knowledge extracted from software data residing in various repositories can be combined and used to enable effective decision making and save considerable time and effortthrough software reuse. Mining Software Engineering Data for Software Reuse can also prove handy for graduate-level students in software engineering.

Zielgruppe

Research

Autoren/Hrsg.

Symeonidis, Andreas L.

Diamantopoulos, Themistoklis

Fachgebiete

• Mathematik | Informatik EDV | Informatik Angewandte Informatik Computeranwendungen in Wissenschaft & Technologie
• Mathematik | Informatik EDV | Informatik Angewandte Informatik Wirtschaftsinformatik
• Technische Wissenschaften Technik Allgemein Computeranwendungen in der Technik
• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Software Engineering
• Mathematik | Informatik EDV | Informatik Betriebssysteme Linux Betriebssysteme, Open Source Betriebssysteme
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining
• Wirtschaftswissenschaften Betriebswirtschaft Wirtschaftsinformatik, SAP, IT-Management

Inhaltsverzeichnis

Part 1: Introduction and Background.- Introduction.- Theoretical Background and State-of-the-art.- Part II: Requirements Mining.- Modelling Software Requirements.- Mining Software Requirements.- Part III: Source Code Mining.- Source Code Indexing for Component Reuse.- Mining Source Code for Component Reuse.- Mining Source Code for Snippet Reuse.- Mining Solutions for Extended Snippet Reuse.- Part IV: Quality Assessment.- Providing Reusability-aware Recommendations.- Assessing the Reusability of Source Code Components.- Part V: Conclusion and Future Work.- Conclusion.- Future Work.- Bibliography