基于数据挖掘的软件缺陷故障智能定位与识别方法

Fang Wang
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引用次数: 1

摘要

随着时代的进步,计算机技术也在不断的进步,人们对软件功能的要求也在不断的提高,而随着软件功能越来越复杂,开发人员在技术上受到限制,团队协作也没有默契的配合。如此等等,所以在软件开发过程中,一些错误和问题必然会导致软件缺陷。本文的目的是研究基于数据挖掘的软件缺陷智能定位与识别方法。本文首先研究了国内外软件缺陷故障智能定位技术,分析了传统软件缺陷检测和故障检测的不足,然后详细介绍了数据挖掘技术,最后对软件缺陷预测技术进行了深入研究。通过对多项技术的深入研究,减少了软件设备的事故,延长了软件设备的使用寿命。根据本文的实验,本文提出的软件缺陷定位采用两种方法进行比较。将第一个错误集作为度量后续错误集软件错误定位成本的单位。第一个误差集1F包含19个人工注入的误差程序,得到的平均定位成本为3.75%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Software Defect Fault Intelligent Location and Identification Method Based on Data Mining
With the advancement of the times, computer technology is also constantly improving, and people's requirements for software functions are also constantly improving, and as software functions become more and more complex, developers are technically limited and teamwork is not tacitly coordinated. And so on, so in the software development process, some errors and problems will inevitably lead to software defects. The purpose of this paper is to study the intelligent location and identification methods of software defects based on data mining. This article first studies the domestic and foreign software defect fault intelligent location technology, analyzes the shortcomings of traditional software defect detection and fault detection, then introduces data mining technology in detail, and finally conducts in-depth research on software defect prediction technology. Through in-depth research on several technologies, it reduces the accidents of software equipment and delays its service life. According to the experiments in this article, the software defect location proposed in this article uses two methods to compare. The first error set is used as a unit to measure the subsequent error set software error location cost. The first error set 1F contains 19 A manually injected error program, and the average positioning cost obtained is 3.75%.
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CiteScore
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