Code-based prioritization: a pre-testing effort to minimize post-release failures

  • Authors:

  • Mitrabinda Ray;Durga Prasad Mohapatra

  • Affiliations:

  • Department of Computer Science and Engineering, National Institute of Technology, Rourkala, India 769008;Department of Computer Science and Engineering, National Institute of Technology, Rourkala, India 769008

  • Venue:
  • Innovations in Systems and Software Engineering
  • Year:
  • 2012

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Abstract

Improving the efficiency of the testing process is a challenging goal. Prior work has shown that often a small number of errors account for the majority of software failures; and often, most errors are found in a small portion of a source code. We argue that prioritizing code elements before conducting testing can help testers focus their testing effort on the parts of the code most likely to expose errors. This can, in turn, promote more efficient testing of software. Keeping this in view, we propose a testing effort prioritization method to guide tester during software development life cycle. Our approach considers five factors of a component such as Influence value, Average execution time, Structural complexity, Severity and Value as inputs and produce the priority value of the component as an output. Once all components of a program have been prioritized, testing effort can be apportioned so that the components causing more frequent and/or more severe failures will be tested more thoroughly. Our proposed approach is effective in guiding testing effort as it is linked to external measure of defect severity and business value, internal measure of frequency and complexity. As a result, the failure rate is decreased and the chance of severe type of failures is also decreased in the operational environment. We have conducted experiments to compare our scheme with a related scheme. The results establish that our proposed approach that prioritizes the testing effort within the source code is able to minimize highly severed types of failures and also number of failures at the post-release time of a software system.