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Automated Software Engineering

, Volume 26, Issue 4, pp 795–837 | Cite as

How effective are existing Java API specifications for finding bugs during runtime verification?

  • Owolabi LegunsenEmail author
  • Nader Al Awar
  • Xinyue Xu
  • Wajih Ul Hassan
  • Grigore Roşu
  • Darko Marinov
Article
  • 50 Downloads

Abstract

Runtime verification can be used to find bugs early, during software development, by monitoring test executions against formal specifications (specs). The quality of runtime verification depends on the quality of the specs. While previous research has produced many specs for the Java API, manually or through automatic mining, there has been no large-scale study of their bug-finding effectiveness. Our conference paper presented the first in-depth study of the bug-finding effectiveness of previously proposed specs. We used JavaMOP to monitor 182 manually written and 17 automatically mined specs against more than 18K manually written and 2.1M automatically generated test methods in 200 open-source projects. The average runtime overhead was under \(4.3{\times }\). We inspected 652 violations of manually written specs and (randomly sampled) 200 violations of automatically mined specs. We reported 95 bugs, out of which developers already fixed or accepted 76. However, most violations, 82.81% of 652 and 97.89% of 200, were false alarms. Based on our empirical results, we conclude that (1) runtime verification technology has matured enough to incur tolerable runtime overhead during testing, and (2) the existing API specifications can find many bugs that developers are willing to fix; however, (3) the false alarm rates are worrisome and suggest that substantial effort needs to be spent on engineering better specs and properly evaluating their effectiveness. We repeated our experiments on a different set of 18 projects and inspected all resulting 742 violations. The results are similar, and our conclusions are the same.

Keywords

Runtime verification Monitoring-oriented programming Specification quality Software testing Empirical study 

Notes

Acknowledgements

Karl Hajal, Milica Hadzi-Tanovic and Igor Lima helped with inspecting violations in our validation study and submitting pull requests. We thank Alex Gyori, Farah Hariri, Cosmin Radoi, and August Shi for feedback on early drafts of this paper, Rahul Gopinath for discussions and help with Randoop, and He Xiao and Yi Zhang for help with JavaMOP. We also thank all authors of papers who replied to our emails concerning their mined specs. This research was partially supported by the NSF Grants CCF-1421503, CCF-1421575, CCF-1438982, CCF-1439957, CNS-1646305, CNS-1740916, and CCF-1763788. Wajih Ul Hassan was partially supported by the Sohaib and Sara Abassi Fellowship. We gratefully acknowledge support for research on testing from Microsoft and Qualcomm.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.University of Illinois at Urbana-ChampaignUrbanaUSA
  2. 2.American University of BeirutBeirutLebanon

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