Test Case Generation for Data Flow Testing using Cuckoo Search Algorithm
Sanjiv Sharma1, S.A.M. Rizvi2, Vineet Kumar Sharma3
1Sanjiv Sharma, Department of Computer Science & Engineering, KIET Group of Institutions, Ghaziabad (U.P), India.
2S.A.M Rizvi, Department of Computer Science, Jamia Millia Islamia University, (New Delhi), India.
3Vineet Kumar Sharma, Department of Computer Science & Engineering, KIET Group of Institutions, Ghaziabad (U.P), India.
Manuscript received on 17 October 2019 | Revised Manuscript received on 25 October 2019 | Manuscript Published on 02 November 2019 | PP: 2953-2964 | Volume-8 Issue-2S11 September 2019 | Retrieval Number: B13770982S1119/2019©BEIESP | DOI: 10.35940/ijrte.B1377.0982S1119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Software testing consumes the major portion of the total efforts required for software development. This activity is very time consuming and labor intensive. It is very hard to do testing in optimal manner. In this paper a new approach is proposed, which uses the nature inspired stochastic algorithm called Cuckoo Search Algorithm (CSA) for the automatic generation of test data for data flow testing. This approach considers all def-use as test adequacy criteria. For assistance to CSA in the state space a new fitness function is also proposed by using the concept of dominator tree and branch distance in a CFG. To validate the proposed approach experiments are carried out on 10 benchmarked programs and findings are contrasted with earlier work done in this domain. Further in order to prove that proposed approach performs better than the above mentioned approaches a statistical difference test (T-test) is also performed.
Keywords: Software Testing, Cuckoo Search Algorithm, Data Flow testing, Dominance tree, Branch Distance.
Scope of the Article: Data Base Management System