Applications of defect prevention in software development

1990 ◽  
Vol 8 (2) ◽  
pp. 164-168 ◽  
Author(s):  
R.G. Mays
Keyword(s):  
Software Development ◽  
Defect Prevention

Software Defect Prevention through Orthogonal Defect Classification (ODC)

2013 ◽  
Vol 11 (3) ◽  
pp. 2393-2400 ◽  
Author(s):  
Sakthi Kumaresh ◽  
R Baskaran
Keyword(s):  
Software Development ◽  
Arrival Rate ◽  
Defect Classification ◽  
Software Defect ◽  
Development Life Cycle ◽  
Software Product ◽  
Prevention Model ◽  
Defect Prevention ◽  
To Come ◽  
Orthogonal Defect Classification

“Quality is never an accident; it is always the result of intelligent effort” [10]. In the process of making quality software product, it is necessary to have effective defect prevention process, which will minimize the risk of making defects /errors in software deliverables. An ideal approach would involve effective software development process with an integrated defect prevention process. This paper presents a Defect Prevention Model in which Defect Prevention Process(DPP) is integrated into software development life cycle to reduce the defects at early stages itself, thereby reducing the defect arrival rate as the project progresses to the subsequent stages. Orthogonal Defect Classification (ODC) scheme involving defect trigger, defect type etc. are discussed in this work to illustrate how ODC can be used in the defect prevention process. ODC can be used to measure development progress with respect to product quality and identify process problems, which will help to come out with “Best Practices” to be followed to eradicate the defects in the subsequent projects.

SOFTWARE DEFECT PREDICTION USING INTERTRANSACTION ASSOCIATION RULE MINING

2009 ◽  
Vol 19 (06) ◽  
pp. 747-764 ◽  
Author(s):  
CHING-PAO CHANG ◽  
CHIH-PING CHU
Keyword(s):  
Software Development ◽  
Prediction Model ◽  
Association Rule ◽  
Association Rule Mining ◽  
Rule Mining ◽  
High Severity ◽  
Software Defect ◽  
Novel Approach ◽  
Defect Prevention ◽  
Significant Effort

Reducing the variance between expectation and execution of software processes is an essential activity for software development, in which the Causal Analysis is a conventional means of detecting problems in the software process. However, significant effort may be required to identify the problems of software development. Defect prevention prevents the problems from occurring, thus lowering the effort required in defect detection and correction. The prediction model is a conventional means of predicting the problems of subsequent process actions, where the prediction model can be built from the performed actions. This study proposes a novel approach that applies the Intertransaction Association Rule Mining techniques to the records of performed actions in order to discover the patterns that are likely to cause high severity defects. The discovered patterns can then be applied to predict the subsequent actions that may result in high severity defects.

Using work-centered specifications to integrate cognitive requirements into software development

2006 ◽  
Author(s):  
Jeffrey Wampler ◽  
Emilie Roth ◽  
Randall Whitaker ◽  
Kendall Conrad ◽  
Mona Stilson ◽  
...  
Keyword(s):  
Software Development
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