Software Testing, Verification and Reliability

Cover image for Vol. 25 Issue 2

March 2015

Volume 25, Issue 2

Pages i–ii, 73–163

  1. Issue Information

    1. Top of page
    2. Issue Information
    3. Editorial
    4. Research Articles
    1. You have free access to this content
      Issue Information (pages i–ii)

      Article first published online: 22 FEB 2015 | DOI: 10.1002/stvr.1551

  2. Editorial

    1. Top of page
    2. Issue Information
    3. Editorial
    4. Research Articles
    1. You have free access to this content
  3. Research Articles

    1. Top of page
    2. Issue Information
    3. Editorial
    4. Research Articles
    1. Directed test suite augmentation: an empirical investigation (pages 77–114)

      Zhihong Xu, Yunho Kim, Moonzoo Kim, Myra B. Cohen and Gregg Rothermel

      Article first published online: 5 NOV 2014 | DOI: 10.1002/stvr.1562

      Thumbnail image of graphical abstract

      Our empirical results show that the primary factor affecting the effectiveness and efficiency of test case augmentation techniques is the choice of test case generation algorithm. The manner in which new and existing test cases are used also usually affects efficiency and in a few cases affects effectiveness. The order in which target code elements are considered affects the efficiency of genetic test case generation techniques but has no affect on concolic test case generation techniques.

    2. Reducing execution profiles: techniques and benefits (pages 115–137)

      Joan Farjo, Rawad Abou Assi and Wes Masri

      Article first published online: 1 DEC 2014 | DOI: 10.1002/stvr.1563

      Thumbnail image of graphical abstract

      This work studied the impact of the size of execution profiles. It presented several reduction techniques and comparatively evaluated them by measuring the reduction rate, information loss, and impact on two software analysis techniques. The results were promising as the average reduction rate ranged from 92% to 98%, most techniques were lossless or slightly lossy, and reducing execution profiles was shown to benefit software analysis in terms of efficiency and/or effectiveness.

    3. Automated metamorphic testing of variability analysis tools (pages 138–163)

      Sergio Segura, Amador Durán, Ana B. Sánchez, Daniel Le Berre, Emmanuel Lonca and Antonio Ruiz-Cortés

      Article first published online: 13 JAN 2015 | DOI: 10.1002/stvr.1566

      Thumbnail image of graphical abstract

      We present an approach for the automated detection of faults in variability analysis tools overcoming the oracle problem. Our work enables the generation of random variability models together with their exact set of valid configurations. Test data are generated from scratch using stepwise transformations and assuring that certain metamorphic relations hold at each step. For the evaluation, we automatically tested several tools in three domains: feature models, common upgradeability description format documents, and Boolean formulas. We detected 19 real bugs in 7 tools.

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