• DocumentCode
    2209554
  • Title

    A theoretical and empirical study of EFSM dependence

  • Author

    Androutsopoulos, Kelly ; Gold, Nicolas ; Harman, Mark ; Li, Zheng ; Tratt, Laurence

  • Author_Institution
    Dept. of Comput. Sci., King´´s Coll. London, London, UK
  • fYear
    2009
  • fDate
    20-26 Sept. 2009
  • Firstpage
    287
  • Lastpage
    296
  • Abstract
    Dependence analysis underpins many activities in software maintenance such as comprehension and impact analysis. As a result, dependence has been studied widely for programming languages, notably through work on program slicing. However, there is comparatively little work on dependence analysis at the model level and hitherto, no empirical studies. We introduce a slicing tool for extended finite state machines (EFSMs) and use the tool to gather empirical results on several forms of dependence found in ten EFSMs, including well-known benchmarks in addition to real-world EFSM models. We investigate the statistical properties of dependence using statistical tests for correlation and formalize and prove four of the empirical findings arising from our empirical study. The paper thus provides the maintainer with both empirical data and foundational theoretical results concerning dependence in EFSM models.
  • Keywords
    finite state machines; program slicing; software maintenance; software tools; EFSM dependence theoretical study; comprehension analysis; correlation statistical test; dependence statistical property; extended finite state machine; impact analysis; program slicing; programming language; slicing tool; software maintenance; Application software; Automata; Benchmark testing; Computer languages; Computer science; Debugging; Educational institutions; Software maintenance; Software testing; System testing; Dependence Analysis; EFSM; Slicing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Software Maintenance, 2009. ICSM 2009. IEEE International Conference on
  • Conference_Location
    Edmonton, AB
  • ISSN
    1063-6773
  • Print_ISBN
    978-1-4244-4897-5
  • Electronic_ISBN
    1063-6773
  • Type

    conf

  • DOI
    10.1109/ICSM.2009.5306309
  • Filename
    5306309