• DocumentCode
    176225
  • Title

    Program Slicing in the Presence of Preprocessor Variability

  • Author

    Kanning, F. ; Schulze, S.

  • Author_Institution
    Tech. Univ. Braunschweig, Braunschweig, Germany
  • fYear
    2014
  • fDate
    Sept. 29 2014-Oct. 3 2014
  • Firstpage
    501
  • Lastpage
    505
  • Abstract
    Program slicing is a common means to support developers in examining the source code with respect to debugging, program comprehension, or regression testing. While a vast amount of techniques exist, they are mostly tailored to single software systems. However, with the increasing importance of variable and highly-configurable systems, such as the Linux kernel, the number of software variants, subject to analysis, increases dramatically. Consequently, it is infeasible to apply slicing on each variant in isolation. To overcome this problem, we propose variability-aware slicing, a technique that can deal with source code variability, specifically conditional compilation as introduced by the C preprocessor. Particularly, we provide details of our variability-aware dependence analysis for program slicing, point out benefits of our slicing technique, and mention current limitations and future work.
  • Keywords
    Linux; operating system kernels; program debugging; program slicing; program testing; regression analysis; source code (software); C preprocessor; Linux kernel; conditional compilation; debugging; preprocessor variability; program comprehension; program slicing; regression testing; software variants; source code variability; variability-aware dependence analysis; variability-aware slicing; Aggregates; Computer languages; Equations; Feature extraction; Software systems; Testing; C preprocessor; program slicing; variability-aware analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Software Maintenance and Evolution (ICSME), 2014 IEEE International Conference on
  • Conference_Location
    Victoria, BC
  • ISSN
    1063-6773
  • Type

    conf

  • DOI
    10.1109/ICSME.2014.82
  • Filename
    6976126