Quantifying the Effectiveness of Testing Efforts on Software Fault Detection with a Logit Software Reliability Growth Model

Quantifying the effects of software testing metrics such as the number of test runs on the fault detection ability is quite important to design and manage effective software testing. This paper focuses on the regression model which represents the causal relationship between the software testing metrics and the fault detection probability. In a numerical experiment, we perform the quantitative estimation of the causal relationship through the quantization of software testing metrics.

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