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Efficient Prediction Method of Defect of Monitor Configuration Software
Author(s) -
Yan Wang
Publication year - 2019
Publication title -
journal of advanced computational intelligence and intelligent informatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.172
H-Index - 20
eISSN - 1343-0130
pISSN - 1883-8014
DOI - 10.20965/jaciii.2019.p0340
Subject(s) - computer science , software , support vector machine , software bug , software sizing , verification and validation , data mining , software metric , genetic algorithm , reliability engineering , software quality , machine learning , software construction , software system , software development , artificial intelligence , operating system , statistics , mathematics , engineering
In order to solve the problem of low efficiency in software operation, we need to research the defect prediction of monitoring configuration software. The current method has the low efficiency in the defect prediction of software. Therefore, this paper proposed the software defect prediction method based on genetic optimization support vector machines. This method carried out feature selection for the measure of complexity of software, and built software defect prediction model of genetic optimized support vector machine, and completed the research on the efficient prediction method of software defects. Experimental results show that the proposed method improves the quality of software effectively.

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