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Smell Detection Agent Optimization Approach to Path Generation in Automated Software Testing

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Abstract

Software testing is the most crucial stage in the software development process. Structural testing, functional testing and models that even support hybrid testing are different software testing techniques. Basic path testing, the most significant structural testing approach, is focused on evaluating software source code. The method emphasizes developing test data inputs to produce all feasible and efficient test paths that connect to all nodes and edges of the graph. The objective is to define the number of independent paths that can define the number of test cases needed to maximize test coverage. It ensured the execution of every statement and condition at least once. A nature-inspired Smell Detection Agent (SDA) algorithm is proposed in this paper to select all paths and prioritize the feasible solution. This algorithm is an optimization algorithm suitable for identifying optimal paths with priority. The concept is derived from the natural behaviour of canines that identified optimal path from source to the destination. The SDA algorithm is based on the evaporation of smell molecules in the form of gas and the perception capability of a smelling agent. The number of linearly independent paths through a programme module is measured by creating a Control Flow Graph of the code, which measures cyclomatic complexity. SDA algorithm gives significant increases in performance while considering the cyclomatic complexity. Complexity analysis of SDA trends to be in the O(E+V log V), while the competitor algorithms have an exponential growth of O(n\(^2\)). Various experiments were also carried out to emphasis the relevance of the proposed method. Ten different benchmarked applications has been taken for experimental analysis and it was observed to have an increased path coverage of 8% when SDA was used over the traditional methods. Also, the time complexity was reduced by 22%, which shows the powerfulness of the proposed SDA algorithm.

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Supplementary materials are available in http://www.mirworks.in/downloads.php.

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Acknowledgments

Authors would like to thank, Government of India for issuing Copyright for the algorithm Smell Detection Agent based Optimization Algorithm and Indian Patent to the work Bio-inspired Controller for Finding Disjoint Paths in Software Defined Networks, which were the basic concepts used in the development of the proposed work. The authors would also like to extend gratitude to all researchers affiliated with the Machine Intelligence Research(MIR) Laboratory for their support during each phase of this work.

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Authors and Affiliations

  1. Department of Computer Science, Thiruvananthapuram, University of Kerala, Thiruvananthapuram, India

    S. S. Vinod Chandra

  2. Department of Computer Engineering, Government Polytechnic College, Punalur, India

    S. Saju Sankar

  3. Department of Computer Science and Engineering, Muthoot Institute of Technology and Science, Kochi, India

    H. S. Anand

Authors
  1. S. S. Vinod Chandra
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  2. S. Saju Sankar
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  3. H. S. Anand
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Contributions

Vinod developed the problem statement, conceptualized this study and developed the methodology. Anand has curated the data and was involved in the methodology implementation. Saju implemented and wrote the initial manuscript along with curation.

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Correspondence to S. S. Vinod Chandra.

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Chandra, S.S.V., Sankar, S.S. & Anand, H.S. Smell Detection Agent Optimization Approach to Path Generation in Automated Software Testing. J Electron Test 38, 623–636 (2022). https://doi.org/10.1007/s10836-022-06033-8

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  • DOI: https://doi.org/10.1007/s10836-022-06033-8

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