Fuzzy Logic Based Model to Predict Per Phase Software Defect
Misha Kakkar1, Sarika Jain2, Abhay Bansal3, P. S. Grover4
1Misha Kakkar, Department of Computer Science and Engineering, Amity University Uttar Pradesh (Noida), India.
2Dr. Sarika Jain, Amity Institute of Information Technology, Amity University Uttar Pradesh (Noida), India.
3Prof. (Dr.) Abhay Bansal, Department of Computer Science and Engineering, Amity University Uttar Pradesh (Noida), India.
4Prof. (Dr.) P. S. Grover, KIIT Group of Colleges, Gurgaon (Haryana), India.
Manuscript received on 09 August 2019 | Revised Manuscript received on 17 August 2019 | Manuscript Published on 26 August 2019 | PP: 47-51 | Volume-8 Issue-9S August 2019 | Retrieval Number: I10060789S19/19©BEIESP DOI: 10.35940/ijitee.I1006.0789S19
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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 reliability is expressed as the probability of software to function properly under specified condition for a specified time period. A basic method to evaluate the software reliability is to check the presence of defects in the software. The presence of defect can be calculated as defect density measured defined as total number of defects present in the software divided by the size of the software. The paper proposes a fuzzy logic based model to predict per phase software defect density. The model uses 3 relevant software metrics per SDLC phase. Defect density prediction is a useful measure, which indicates the critical modules of the project and helps software teams to plan their resources in an efficient manner. The proposed model results are better in comparison with existing literature in the same domain when compared using MRE performance measure on 20 project dataset.
Keywords: Defect Prediction, Fuzzy logic, Metrics, Phase-wise, SDLC.
Scope of the Article: Fuzzy Logics