Defect prevention in software processes: An action-based approach

Chang, Ching-Pao; Chu, Chih‐Ping

doi:10.1016/j.jss.2006.09.009

Cited by 23 publications

(27 citation statements)

References 19 publications

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“…The Bayesian Net (BN) can be applied in each development lifecycle to predict the number of software defects of software products to facilitate software testing [25]. Besides identifying the components that may generate defects, the Action-Based Defect Prediction (ABDP) applies classification tree techniques on the records of performed actions to identify subsequent actions that are likely to cause defects [8]. Association rule mining and classification tree are two common data mining approaches, which can be used to discover knowledge of the software process.…”

Section: Software Defect Predictionmentioning

confidence: 99%

“…There are many approaches can be used to record the execution of software process, such as the TychoMetrics uses the Measurement Object Model to define measurement schema [32] and the Task Element Decomposition (TED) divides tasks into operations based on their size and complexity [33]. This study uses the same attributes to record actions and reported defects as ABDP [8].…”

Section: Software Defect Patternsmentioning

confidence: 99%

“…Action-Based Defect Prediction 0950-5849/$ -see front matter Ó 2008 Elsevier B.V. All rights reserved. doi:10.1016/j.infsof.2008.04.008 (ABDP) performs classification mining on the records of defects and actions to construct prediction models [8]. The ABDP approach includes a set of attributes to describe the actions within a software process, where an action is defined as an operation performed as part of a task in the Work Breakdown Structure (WBS) of the project, while a defect is defined as software flaws, such as the errors in documents, bugs in codes and designs, software system failures and other problems in processes causing software failure.…”

Section: Introductionmentioning

confidence: 99%

“…The iterative process forms the inprocess software defect prediction, which can reduce the variance of data from different projects. To demonstrate the performance of the ARDP, this study applies ARDP to a data set of a business project developing an Attendance Management System for the Customs Office of the Ministry of Finance of Taiwan (AMS-COMFT) [8]. The rest of this paper is organized as follows.…”

Section: Introductionmentioning

confidence: 99%

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Integrating in-process software defect prediction with association mining to discover defect pattern

Chang

Chu

Yeh

2009

Information and Software Technology

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Section: Software Defect Predictionmentioning

confidence: 99%

Section: Software Defect Patternsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Integrating in-process software defect prediction with association mining to discover defect pattern

Chang

Chu

Yeh

2009

Information and Software Technology

Self Cite

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“…When these defects are not detected or when they are detected late, there are consequences such as delays in delivery dates, inconvenience to the customer, and increased cost and effort; additionally, significant efforts may be required to correct or find those defects later in software development [2]. Once the defect is recognized, it is important to determine its causes by means of an analysis.…”

Section: Introductionmentioning

confidence: 99%

“Defect Root-Cause Analysis and 1+n Procedure” technique to improve software quality

Honda

Yamada

2012

Int J Syst Assur Eng Manag

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Very Small Entities (VSE) dedicated to software development lack of enough resources to adopt causal analysis practices, defined in models as CMMI, due to their complexity and costs. It is important to detect the generated defects in the development process, and to make a systematic analysis aimed at determining its causes. However, identifying those root causes is an arduous task, and failing to do so leads to wrong decisions that either fail to solve the problem or even make it worse. On this basis, this paper proposes a causal analysis procedure focused on small organizations PAC-DS (according to its initials in Spanish), which includes activities aimed at identifying the defects causes. After its evaluation in a preliminary case study, the utility of the procedure was evidenced.Keywords: Causal Analysis; Software Engineering; Software Process Improvement; Small Software Development Organizations. ResumenLas pequeñas organizaciones desarrolladoras de software no cuentan con recursos suficientes para adoptar prácticas de análisis causal, definidas en modelos como CMMI, debido a la complejidad y el costo de estas. Es importante detectar los defectos generados en el proceso de desarrollo y hacer un análisis sistemático para determinar sus causas; pero identificar esas causas principales es una labor difícil, y no lograrlo lleva a tomar decisiones erróneas que no resuelven la problemática presentada o, incluso, la empeoran. A causa de lo anterior, este artículo propone un procedimiento de análisis causal enfocado en pequeñas organizaciones (PAC-DS) que incorpora actividades para identificar las causas de los defectos. Tras su evaluación en un caso de estudio preliminar, se evidenció la utilidad del procedimiento.Palabras clave: Análisis causal; Ingeniería de Software; Mejora de procesos software; Pequeñas organizaciones de desarrollo software.* Universidad del Cauca (Popayán-Cauca, Colombia). kyzuniga@unicauca.edu.co. ORCID: 0000-0002-5181-1327. ** M. Sc. Universidad del Cauca (Popayán-Cauca, Colombia). cardila@unicauca.edu.co. *** Ph. D. Universidad del Cauca (Popayán-Cauca, Colombia). fjpino@unicauca.edu.co. Causal analysis procedure focused on small software development organizations ResumoAs pequenas organizações desenvolvedoras de software não contam com recursos suficientes para adotar práticas de análise causal, definidas em modelos como CMMI, devido à complexidade e o custo que apresentam. É importante detectar os defeitos gerados no processo de desenvolvimento e fazer uma análise sistemática para determinar suas causas; porém identificar essas causas principais é um labor difícil, e não lográ-lo leva a tomar decisões errôneas que não resolvem a problemática apresentada ou, inclusive, pioram-na. Consequentemente, este artigo propõe um procedimento de análise causal enfocado em pequenas organizações (PAC-DS) que incorpora atividades para identificar as causas dos defeitos. Após sua avaliação em um caso de estudo preliminar, evidenciouse a utilidade do procedimento.Palavras chave: Análise causal; En...

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A novel software defect prediction based on atomic class-association rule mining

Shao

Liu

Wang

et al. 2018

Expert Systems with Applications

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Defect prevention in software processes: An action-based approach

Cited by 23 publications

References 19 publications

Integrating in-process software defect prediction with association mining to discover defect pattern

Integrating in-process software defect prediction with association mining to discover defect pattern

“Defect Root-Cause Analysis and 1+n Procedure” technique to improve software quality

A novel software defect prediction based on atomic class-association rule mining

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