Towards Reliable Eager Test Detection: Practitioner Validation and a Tool Prototype

Context: Existing tools for detecting eager tests produce many false positives, rendering them unreliable for practitioners. To address this, our previous work introduced a novel definition of the Eager Test smell and a heuristic for more effective identification. Comparing the heuristic’s results with existing detection rules revealed eight test patterns where the rules misclassified the presence or absence of eager tests.Objective: We aim to gather practitioners’ feedback on our heuristic’s assessment of these eight test patterns and operationalize the heuristic in a tool we named EagerID.Method: We conducted a survey to collect practitioners’ feedback on the eight identified test patterns and developed EagerID to detect eager tests in Java unit test cases using JUnit. We also preliminarily evaluated EagerID on 300 test cases, which were manually analyzed in our previous study.Results: Our survey received 23 responses from practitioners with a wide range of experience. We found that most practitioners agreed with the assessment of our heuristic. Furthermore, the preliminary evaluation of EagerID returned high precision (100%), recall (91.76%), and F-Score (95.70%).Conclusion: Our survey findings highlight the practical relevance of the heuristic. The preliminary evaluation of the EagerID tool confirmed the heuristic’s potential for automation. These findings suggest that the heuristic provides a solid foundation for both manual and automated detection.