- author = "Wasif Afzal",
- title = "Search-Based Prediction of Software Quality: Evaluations And Comparisons",
- school = "School of Computing, Blekinge Institute of Technology",
- year = "2011",
- address = "Sweden",
- month = "5 " # may,
- keywords = "genetic algorithms, genetic programming, SBSE",
-
URL = "
http://www.bth.se/fou/forskinfo.nsf/0/dd0dcce8cc126a52c125784500410306/$file/Dis%20Wasif%20Afzal%20thesis.pdf",
- isbn13 = "978-91-7295-203-4",
- size = "313 pages",
-
abstract = "Software verification and validation (V&V) activities
are critical for achieving software quality; however,
these activities also constitute a large part of the
costs when developing software. Therefore efficient and
effective software V&V activities are both a priority
and a necessity considering the pressure to decrease
time-to-market and the intense competition faced by
many, if not all, companies today. It is then perhaps
not unexpected that decisions that affects software
quality, e.g., how to allocate testing resources,
develop testing schedules and to decide when to stop
testing, needs to be as stable and accurate as
possible.
The objective of this thesis is to investigate how search-based techniques can support decision-making and help control variation in software V&V activities, thereby indirectly improving software quality. Several themes in providing this support are investigated: predicting reliability of future software versions based on fault history; fault prediction to improve test phase efficiency; assignment of resources to fixing faults; and distinguishing fault-prone software modules from non-faulty ones. A common element in these investigations is the use of search-based techniques, often also called metaheuristic techniques, for supporting the V&V decision-making processes. Search-based techniques are promising since, as many problems in real world, software V&V can be formulated as optimisation problems where near optimal solutions are often good enough. Moreover, these techniques are general optimization solutions that can potentially be applied across a larger variety of decision-making situations than other existing alternatives. Apart from presenting the current state of the art, in the form of a systematic literature review, and doing comparative evaluations of a variety of metaheuristic techniques on large-scale projects (both industrial and open-source), this thesis also presents methodological investigations using search-based techniques that are relevant to the task of software quality measurement and prediction.
The results of applying search-based techniques in large-scale projects, while investigating a variety of research themes, show that they consistently give competitive results in comparison with existing techniques. Based on the research findings, we conclude that search-based techniques are viable techniques to use in supporting the decision-making processes within software V&V activities. The accuracy and consistency of these techniques make them important tools when developing future decision support for effective management of software V&V activities.",
-
notes = "Advisors, Dr. Richard Torkar and Dr. Robert Feldt.
http://www.bth.se/eng/calendar.nsf/allaDok/9984ce8a1e18e8ecc125782a004d4167!OpenDocument
Doctoral Dissertation Series No. 2011:06",
