Analyzing individual performance of source code review using reviewers' eye movement

This paper proposes to use eye movements to characterize the performance of individuals in reviewing source code of computer programs. We first present an integrated environment to measure and record the eye movements of the code reviewers. Based on the fixation data, the environment computes the line number of the source code that the reviewer is currently looking at. The environment can also record and play back how the eyes moved during the review process. We conducted an experiment to analyze 30 review processes (6 programs, 5 subjects) using the environment. As a result, we have identified a particular pattern, called scan, in the subjects' eye movements. Quantitative analysis showed that reviewers who did not spend enough time for the scan tend to take more time for finding defects.