Reuse-Based Test Recommendation in Software Engineering


Janjic, Werner



Document Type: Book
Year of publication: 2014
Place of publication: München
Publishing house: Dr. Hut
ISBN: 978-3-8439-1673-8
Publication language: English
Institution: School of Business Informatics and Mathematics > Softwaretechnik (Atkinson)
Subject: 004 Computer science, internet
Subject headings (SWD): Software Testing
Individual keywords (German): Wiederverwendung , Software Testing , Testdaten , Recommendation System , JUnit
Keywords (English): Reuse , Software Testing , Test Data , Recommendation System , Continuous Speculative Testing , Test Reuse Environment , Test Reuse
Abstract: Still today, the development of effective and high-quality software tests is an expensive and very labor intensive process. It demands a high amount of problem awareness, domain knowledge and concentration from human software testers. Therefore, any technology that can help reduce the manual effort involved in the software testing process -- while ensuring at least the same level of quality -- has the potential to significantly reduce software development and maintenance costs. In this dissertation, we present a new idea for achieving this by reusing the knowledge bound up in existing tests. Over the last two decades, software reuse and code recommendation has received a wide variety of attention in academia and industry, but the research conducted in this area to date has focused on the reuse of application code rather than on the reuse of tests. By switching this focus, this thesis paves the way for the automated extraction of test data and knowledge from previous software projects. In particular, it presents a recommendation approach for software tests that leverages lessons learned from traditional software reuse to make test case reuse suggestions to software engineers while they are working. In contrast to most existing testing-assistance tools, which provide ex post assistance to test developers in the form of coverage assessments and test quality evaluations, our approach offers an automated, proactive, non-intrusive test recommendation system for efficient software test development.
Additional information: Zugl.: Mannheim, Univ., Diss., 2014

Dieser Eintrag ist Teil der Universitätsbibliographie.




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