To Optimized Software Defect Detection And Prediction By Using Soft Computing Techniques

  • M. Thangavel, Dr. R. Pugazhendi
Keywords: Software Defect Prediction (SDP), Feature Selection, Firefly Algorithm (FA), Harmony Search (HS) Algorithm, and Support Vector Machine (SVM).


In the current circumstance slips away in software things are a standard cutoff. This reshaping ought   to be obstructed before all else stages. This cycle needs more thoughts since want close to the early phase and fixing the turns lesser effort and cost. Software Defect Prediction (SDP) is basic for the assertion of software quality moreover to trustworthiness. The aching for defects is a for the most   part remarkable assessment area in software quality masterminding. Feature affirmation is one of the brilliant pre-overseeing methodologies for an application that uses goliath volumes of data. It is the course toward picking the conceivable unimportant brand name which is depended on to be tended to all through the movement of authentic credits. It joins confirmation using the Firefly Algorithm (FA), Harmony Search (HS) evaluation, and classifiers like Support Vector Machine (SVM) are used for portraying the features picked. The part decision that uses the FA-HS can take a gander at  the fragment space for an ideal or a near-ideal region subset for confining a particular hindrance of progress. The affiliation has effective work that has used the joining of the precision from the information of an outline and the rot of the size. The throughput of the evaluation has shown that the proposed procedure can achieve the best precision of the arrangement over that of various constructions.

How to Cite
Dr. R. Pugazhendi, M. T. (2021). To Optimized Software Defect Detection And Prediction By Using Soft Computing Techniques. Design Engineering, 1241-1262. Retrieved from