Prioritization for Regression Testing Using Ant Colony Optimization Based on Test Factors

  • Sheikh Fahad Ahmad
  • Deepak Kumar Singh
  • Preetam Suman
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 624)

Abstract

Regression testing is considered to be one of the most costly, time-taking, and important activity which is performed in an environment with a number of certain restrictions for ensuring the validity of a modified software. Therefore, it becomes necessary to pick the sequence of test cases which is correct as well as it should have the ability to traverse all the faults taking minimum execution time. Prioritizing the test cases helps to achieve performance requirements in which important test cases are executed before than those having lower degree of importance. Studies have shown that prioritization approaches based on test factors like Importance, Volatility, Complexity, Fault Rate, Time, Coverage have good results and also the approaches based on intelligent techniques like Ant Colony, genetic algorithms, have been very promising. Hence, this paper presents a hybrid of these two approaches which first generates the test cases based on the priorities, which are assigned using test factors, and then, the best sequence having least execution time and highest fault rate is calculated by the Ant Colony Optimization algorithm.

Keywords

Ant Colony Optimization (ACO) Regression testing Prioritizing test cases Test factors 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  • Sheikh Fahad Ahmad
    • 1
  • Deepak Kumar Singh
    • 1
  • Preetam Suman
    • 1
  1. 1.Department of CSEIntegral UniversityLucknowIndia

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