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An Empirical Study on Relationship between Requirement Traceability Links and Bugs

Early bug detection reduces the cost of software maintenance; but none of previous works have utilized requirement traceability links (RTLs) as a predictor for bugs. To discuss how to use RTLs to predict the number of bugs, we propose an RTL recovery approach classification based on the ease of the recovery process. Based on that, we investigated the relationship using data from industrial software. We confirmed that classes related to more RTLs tend to have more bugs, and the classification gives better correlations although including RTL in the bug prediction model does not affect the performance. Some class files with no and low RTLs also have bugs; we hypothesize that this occurs because the actual RTL is missing or not established, which is supported by the observation that bugs in these classes are highly correlated with maximum cyclomatic complexity.