Indian Journal of Science and Technology
Year: 2016, Volume: 9, Issue: 45, Pages: 1-9
B. Dhanalaxmi1 *, G. Apparao Naidu2 and K. Anuradha3
1 Department of Information Technology, Institute of Aeronautical Engineering, Dundigal, Hyderabad –500 043, Telangana, India; [email protected] 2Department of Computer Science and Engineering, J. B. Institute of Engineering and Technology, Bhaskar Nagar, Moinabad Mandal, R. R. District, Hyderabad – 500075, Telangana, India; [email protected] 3Department of Computer Science and Engineering, Gokaraju Rangaraju Institute of Engineering and Technology, Nizampet Road, Bachupally, Kukatpally, Hyderabad – 500090, Telangana, India; [email protected]
*Author for correspondence
B. Dhanalaxmi Department of Information Technology, Institute of Aeronautical Engineering, Dundigal, Hyderabad –500 043, Telangana, India; [email protected]
Objective: Software development is a multitask activity performed by a team. Each activity involves with different tasks and complexity. To achieve quality of improvement it is important that each activity task should be fault free. But, finding and correcting faults are most expensive and time consuming. Methods: Software inspection is a static analysis technique which does not required program execution, instead it use inspector to make decision during the development. Findings: But it was observed in literature that inspection has bad records in finding accurate defects in software development. In this paper, we present a novel Fault Prediction Approach (FPA) based on the probabilistic model to improvise the software inspection to detect the defect accurately and cost effective for the quality software development. Application/ Improvement: Inspection is an effective activity to find the defects using empirical data in the initial stage of development. The proposed FPA investigate a probabilistic methods using modified Naive Bayes classification to estimate the probable faults in an experiment context to suggest fault controlling development. Further, the analysis investigates how FPA effectively identifying the faults during the inspection and impact in the quality development performance..
Keywords: Fault Prediction, Probabilistic Model, Software Inspection, Software Quality
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