Search-Based Approaches to Software Fault Prediction and Software Testing

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@MastersThesis{Afzal:Licentiate,
  author =       "Wasif Afzal",
  title =        "Search-Based Approaches to Software Fault Prediction
                 and Software Testing",
  school =       "School of Engineering, Dept. of Systems and Software
                 Engineering, Blekinge Institute of Technology",
  year =         "2009",
  type =         "Licentiate Dissertation",
  address =      "Sweden",
  keywords =     "genetic algorithms, genetic programming, SBSE,
                 Software Engineering, Computer Science, Artificial
                 Intelligence",
  URL =          "http://www.bth.se/fou/forskinfo.nsf/all/f0738b5fc4ca0bbac12575980043def3/$file/Afzal_lic.pdf",
  broken =       "http://www.bth.se/fou/forskinfo.nsf/all/f0738b5fc4ca0bbac12575980043def3?OpenDocument",
  size =         "212 pages",
  isbn13 =       "978-91-7295-163-1",
  language =     "eng",
  oai =          "oai:bth.se:forskinfoF0738B5FC4CA0BBAC12575980043DEF3",
  abstract =     "Software verification and validation activities are
                 essential for software quality but also constitute a
                 large part of software development costs. Therefore
                 efficient and cost-effective software verification and
                 validation activities are both a priority and a
                 necessity considering the pressure to decrease
                 time-to-market and intense competition faced by many,
                 if not all, companies today. It is then perhaps not
                 unexpected that decisions related to software quality,
                 when to stop testing, testing schedule and testing
                 resource allocation needs to be as accurate as
                 possible.

                 This thesis investigates the application of
                 search-based techniques within two activities of
                 software verification and validation: Software fault
                 prediction and software testing for non-functional
                 system properties. Software fault prediction modeling
                 can provide support for making important decisions as
                 outlined above. In this thesis we empirically evaluate
                 symbolic regression using genetic programming (a
                 search-based technique) as a potential method for
                 software fault predictions. Using data sets from both
                 industrial and open-source software, the strengths and
                 weaknesses of applying symbolic regression in genetic
                 programming are evaluated against competitive
                 techniques. In addition to software fault prediction
                 this thesis also consolidates available research into
                 predictive modeling of other attributes by applying
                 symbolic regression in genetic programming, thus
                 presenting a broader perspective. As an extension to
                 the application of search-based techniques within
                 software verification and validation this thesis
                 further investigates the extent of application of
                 search-based techniques for testing non-functional
                 system properties.

                 Based on the research findings in this thesis it can be
                 concluded that applying symbolic regression in genetic
                 programming may be a viable technique for software
                 fault prediction. We additionally seek literature
                 evidence where other search-based techniques are
                 applied for testing of non-functional system
                 properties, hence contributing towards the growing
                 application of search-based techniques in diverse
                 activities within software verification and
                 validation.",
}

Genetic Programming entries for Wasif Afzal

Citations