Software Testing, Verification and Reliability

Cover image for Vol. 26 Issue 4

Early View (Online Version of Record published before inclusion in an issue)

Edited By: Jeff Offutt and Robert M. Hierons

Impact Factor: 1.348

ISI Journal Citation Reports © Ranking: 2014: 35/104 (Computer Science Software Engineering)

Online ISSN: 1099-1689

Associated Title(s): Journal of Software: Evolution and Process, Software Process: Improvement and Practice, Software: Practice and Experience


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  1. Research Articles

    1. Simulink fault localization: an iterative statistical debugging approach

      Bing Liu, Lucia, Shiva Nejati, Lionel C. Briand and Thomas Bruckmann

      Version of Record online: 11 MAY 2016 | DOI: 10.1002/stvr.1605

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      This paper proposes SimFL and iSimFL, fault localization techniques for Simulinkmodels. Our techniques combine statistical debugging and dynamic slicing. In addition, iSimFL (iteratively) utilizes heuristics to determine when test oracle expansion is beneficial for improving the fault localization accuracy. We applied our techniques to industrial automotive Simulink models. We show that the accuracy of our techniques is comparable with that of existing fault localization techniques applied to source code. Further, small test oracle expansions substantially improve debugging accuracy

    2. Prioritizing test cases for early detection of refactoring faults

      Everton L. G. Alves, Patrícia D. L. Machado, Tiago Massoni and Miryung Kim

      Version of Record online: 21 MAR 2016 | DOI: 10.1002/stvr.1603

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      This article's main contributions are as follows:

      • A test case prioritization technique (RBA) centred on detecting refactoring edits faults earlier.
      • An evaluation of the technique by means of two empirical studies. The studies provide statistical evidence that RBA fosters early detection of refactoring-related behavioural changes.
      • A new metric for evaluating how spread is the fault-revealing test cases throughout a prioritized test sequence.
    3. You have full text access to this OnlineOpen article
      Seeding strategies in search-based unit test generation

      José Miguel Rojas, Gordon Fraser and Andrea Arcuri

      Version of Record online: 7 MAR 2016 | DOI: 10.1002/stvr.1601

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      This paper investigates different strategies to seed values (numerical and string constants derived statically and dynamically, type information, and previous solutions) during search-based unit test generation. Results of a large empirical analysis show with strong statistical confidence that the use of appropriate seeding strategies can further improve the code coverage achieved by unit test generation tools.

    4. A general modeling and analysis framework for software fault detection and correction process

      Yu Liu, Duo Li, Lujia Wang and Qingpei Hu

      Version of Record online: 7 MAR 2016 | DOI: 10.1002/stvr.1600

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      In this paper, a framework of software reliability models containing both information from software fault detection process and correction process is studied. The proposed approach is based on Markov model other than a nonhomogeneous Poisson process model. Also, parameter estimation is carried out with weighted least-square estimation method, which emphasizes the influence of later data on the prediction. Two data sets from practical software development projects are applied with the proposed framework, which shows satisfactory performance with the results.


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