一种利用软件度量的定性值建立节点概率表的方法

Proceedings of the 2015 Third International Conference on Computer, Communication, Control and Information Technology (C3IT) Pub Date : 2015-03-16 DOI:10.1109/C3IT.2015.7060187

Chandan Kumar, D. Yadav

{"title":"一种利用软件度量的定性值建立节点概率表的方法","authors":"Chandan Kumar, D. Yadav","doi":"10.1109/C3IT.2015.7060187","DOIUrl":null,"url":null,"abstract":"Recently, Bayesian Belief Network (BBN) becomes one of the most popular choices for uncertainty modeling and has been widely used in software engineering such as defect prediction, reliability and quality prediction, testing effort prediction and software risk assessment. The Node Probability Tables (NPT) play a vital role in BBN. Failure data is not available in the early phases (i.e., phases which occur before testing phase) of software development life cycle (SDLC). However, metrics of early phases of SDLC can be assessed qualitatively. Therefore, an intelligent selection of software metrics also plays a vital role in developing a software defect prediction model using BBN. In this paper, a technique has been proposed to develop the NPT of a BBN using the qualitative value of software metrics.","PeriodicalId":402311,"journal":{"name":"Proceedings of the 2015 Third International Conference on Computer, Communication, Control and Information Technology (C3IT)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A method for developing node probability table using qualitative value of software metrics\",\"authors\":\"Chandan Kumar, D. Yadav\",\"doi\":\"10.1109/C3IT.2015.7060187\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Recently, Bayesian Belief Network (BBN) becomes one of the most popular choices for uncertainty modeling and has been widely used in software engineering such as defect prediction, reliability and quality prediction, testing effort prediction and software risk assessment. The Node Probability Tables (NPT) play a vital role in BBN. Failure data is not available in the early phases (i.e., phases which occur before testing phase) of software development life cycle (SDLC). However, metrics of early phases of SDLC can be assessed qualitatively. Therefore, an intelligent selection of software metrics also plays a vital role in developing a software defect prediction model using BBN. In this paper, a technique has been proposed to develop the NPT of a BBN using the qualitative value of software metrics.\",\"PeriodicalId\":402311,\"journal\":{\"name\":\"Proceedings of the 2015 Third International Conference on Computer, Communication, Control and Information Technology (C3IT)\",\"volume\":\"26 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-03-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2015 Third International Conference on Computer, Communication, Control and Information Technology (C3IT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/C3IT.2015.7060187\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2015 Third International Conference on Computer, Communication, Control and Information Technology (C3IT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/C3IT.2015.7060187","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 2

摘要

近年来，贝叶斯信念网络(BBN)成为不确定性建模最流行的选择之一，在缺陷预测、可靠性和质量预测、测试工作量预测和软件风险评估等软件工程中得到了广泛的应用。节点概率表在BBN中起着至关重要的作用。在软件开发生命周期(SDLC)的早期阶段(即，发生在测试阶段之前的阶段)中，故障数据是不可用的。然而，SDLC的早期阶段的量度可以被定性地评估。因此，在使用BBN开发软件缺陷预测模型时，软件度量的智能选择也起着至关重要的作用。本文提出了一种利用软件度量的定性值来开发BBN的NPT的技术。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

A method for developing node probability table using qualitative value of software metrics

Recently, Bayesian Belief Network (BBN) becomes one of the most popular choices for uncertainty modeling and has been widely used in software engineering such as defect prediction, reliability and quality prediction, testing effort prediction and software risk assessment. The Node Probability Tables (NPT) play a vital role in BBN. Failure data is not available in the early phases (i.e., phases which occur before testing phase) of software development life cycle (SDLC). However, metrics of early phases of SDLC can be assessed qualitatively. Therefore, an intelligent selection of software metrics also plays a vital role in developing a software defect prediction model using BBN. In this paper, a technique has been proposed to develop the NPT of a BBN using the qualitative value of software metrics.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Proceedings of the 2015 Third International Conference on Computer, Communication, Control and Information Technology (C3IT)

自引率

0.00%

发文量