• DocumentCode
    625504
  • Title

    Test Quality Measurement Using TBPP-R

  • Author

    Jun Tang ; Ruilong Huo ; Jiali Yao ; Shaosen Wu

  • Author_Institution
    Greenplum, EMC China COE, Beijing, China
  • fYear
    2013
  • fDate
    18-22 March 2013
  • Firstpage
    48
  • Lastpage
    55
  • Abstract
    Software test quality measurement is the key for software release decision. It is hard to evaluate software test quality because full coverage test is impossible in practice. In this paper, we compare the existing methods for the software test quality measurement and discuss their drawbacks. Then we propose TBPP - a weighted tree based partition and proration method to evaluate software test quality. Furthermore, we evolve this method to TBPP-R by introducing a risk distribution function, which can reveal software test quality more accurately. In our experiments, we compare TBPP-R and TBPP with existing methods in our test projects. The results show that TPBB-R can measure software test quality much more accurately.
  • Keywords
    program testing; software quality; tree data structures; TBPP-R; risk distribution function; software release decision; software test quality evaluation; software test quality measurement; test projects; weighted tree-based partition-and-proration method; Distribution functions; Radio frequency; Software; Software measurement; Software testing; Vectors; Weight measurement; Partition; Proation; Risk; Software Test Quality Measurement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Software Testing, Verification and Validation (ICST), 2013 IEEE Sixth International Conference on
  • Conference_Location
    Luembourg
  • Print_ISBN
    978-1-4673-5961-0
  • Type

    conf

  • DOI
    10.1109/ICST.2013.26
  • Filename
    6569715