Search-Based Prediction of Software Quality: Evaluations And Comparisons

Created by W.Langdon from gp-bibliography.bib Revision:1.4524

  author =       "Wasif Afzal",
  title =        "Search-Based Prediction of Software Quality:
                 Evaluations And Comparisons",
  school =       "School of Computing, Blekinge Institute of
  year =         "2011",
  address =      "Sweden",
  month =        "5 " # may,
  keywords =     "genetic algorithms, genetic programming, SBSE",
  URL =          "$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

                 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

                 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.

                 Doctoral Dissertation Series No. 2011:06",

Genetic Programming entries for Wasif Afzal