• DocumentCode
    3659891
  • Title

    Enhanced Genetic Algorithm for MC/DC test data generation

  • Author

    Ahmed El-Serafy;Ghada El-Sayed;Cherif Salama;Ayman Wahba

  • Author_Institution
    Computers and Systems Engineering Department, Ain-Shams University, Cairo, Egypt
  • fYear
    2015
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    Structural testing is concerned with the internal structures of the written software. The targeted structural coverage criteria are usually based on the criticality of the application. Modified Condition/Decision Coverage (MC/DC) is a structural coverage criterion that was introduced to the industry by NASA. Also, MC/DC comes either highly recommended or mandated by multiple standards, including ISO 26262 from the automotive industry and DO-178C from the aviation industry due to its efficiency in bug finding while maintaining a compact test suite. However, due to its complexity, huge amount of resources are dedicated to fulfilling it. Hence, automation efforts were directed to generate test data that satisfy MC/DC. Genetic Algorithms (GA) in particular showed promising results in achieving high coverage percentages. Our results show that coverage levels could be further improved using a batch of enhancements applied on the GA search.
  • Keywords
    "Genetic algorithms","Sociology","Statistics","Benchmark testing","Industries","Decision feedback equalizers"
  • Publisher
    ieee
  • Conference_Titel
    Innovations in Intelligent SysTems and Applications (INISTA), 2015 International Symposium on
  • Type

    conf

  • DOI
    10.1109/INISTA.2015.7276794
  • Filename
    7276794