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

https://doi.org/10.1016/j.infsof.2008.04.008

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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A neural network approach for early detection of program modules having high risk in the maintenance phase

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Software faults: A quantifiable definition

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Regression via Classification applied on software defect estimation

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Prediction of software development faults in PL/SQL files using neural network models

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Prediction of software failures through logistic regression

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Predicting software defects in varying development lifecycles using Bayesian nets

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Defect prevention in software processes: An action-based approach

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Classification and evaluation of defects in a project retrospective

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Operational anomalies as a cause of safety-critical requirements evolution

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Principles of Data Mining

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Scoring the Data Using Association Rules

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Top 10 list [software development]

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Orthogonal defect classification-a concept for in-process measurements

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Analyzing the subjective interestingness of association rules

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Mining optimized association rules with categorical and numeric attributes

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Defect prevention through defect prediction: a case study at Infosys

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Measurement modeling technology

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Mining quantitative association rules in large relational tables

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Mining quantitative association rules in large relational tables

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Experiences with Defect Prevention

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Japan's Software Factories: A Challenge to U.S. Management

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Japan’s Software Factories: A Challenge to U.S. Management

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The class imbalance problem: A systematic study1

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