Uploaded byThomas Zimmermann
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Predicting Defects using Network Analysis on Dependency Graphs
Network analysis of dependency graphs between code components can help predict defects and prioritize testing. Analyzing dependencies captured metrics like centrality and ego networks that strongly correlated with past defects. These network measures improved prediction of defects, ranking highest risk binaries, and identification of critical "escrow" binaries requiring extra testing over complexity metrics alone, doubling recall of escrow binaries. Combining network and complexity analyses provides more effective defect prediction and testing prioritization to aid new QA managers.
