Software Testing Estimation using Soft Computing Techniques
Amarpal Singh1, Piyush Saxena2, Abhishek Singhal3
1Amarpal Singh, Masters of Technology, CS&E Amity school of Engineering Technology, Amity University Uttar Pradesh, Noida, India.
2Piyush Saxena, Masters of Technology, CS&E Amity school of Engineering Technology, Amity University Uttar Pradesh, Noida, India.
3Abhishek Singhal, CS&E Department, Amity school of Engineering Technology, Amity University Uttar Pradesh, Noida, India.
Manuscript received on June 06, 2013. | Revised Manuscript received on June 25, 2013. | Manuscript published on July 05, 2013. | PP: 58-64 | Volume-3 Issue-3, July 2013. | Retrieval Number: C1630073313/2013©BEIESP
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© The Authors. Published By: 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 development is an extremely composite plus brainstorming action. In previous days programmers wrote programs by means of machine language in which they exhausted their more time in thinking about an exacting machine’s instructions rather than the solution of the problem in their hands. Progressively, program developers switched to advanced stage of programming languages (high-level languages). Software testing is an imperative attribute of software quality. However the prediction of this attribute is a cumbersome process. Therefore various methodologies are proposed so far to estimate the testing time of software. Among them Fuzzy Inference System (FIS) and Adaptive Neuro- Fuzzy Inference System (ANFIS) is one of the sophisticated methods which have immense prediction capability and this paper explores its application to evaluate testing time of the aspect-oriented system. Prediction of testing time is performed by FIS and ANFIS. The results obtained from the current study are compared with adaptive neuro- fuzzy inference system and it is revealed that which model is more useful.
Keywords: Module oriented approach (MOA), Aspect oriented software approach (AOSA), Object Oriented Approach(OOA), Fuzzy Inference System (FIS), Adaptive NeuroFuzzy Inference System (ANFIS).