Android Applications Code Coverage Tools: A Comparative Study
DOI: https://doi.org/10.33003/jobasr
Usman A.
Salihu A.
Muazu A. A.
Eke O.N.
Usman M. A.
Abstract
The widespread adoption of mobile applications necessitates robust quality assurance methods to ensure reliable software behavior. Among these methods, software testing plays a vital role, with code coverage serving as a key metric for evaluating test effectiveness. This study presents a comparative analysis of prominent code coverage tools specifically designed for Android applications. Through an extensive literature review and evaluation of thirteen tools—including Emma, Jacoco, COSMO, WallMauer, and ACVTool—this research highlights their instrumentation strategies, integration capabilities, validation methods, and reporting metrics. The study emphasizes the importance of granularity in coverage (e.g., method, line, and instruction), and the trade-offs between bytecode and source code instrumentation. The findings aim to guide developers and researchers in selecting appropriate tools for enhancing testing coverage in Android app development.
References
Anand, S. (2016). ELLA: a tool for binary instrumentation of Android apps. In: May.
Askar, A., Fleischer, F., Kruegel, C., Vigna, G., & Kim, T. (2025). MALintent: Coverage Guided Intent Fuzzing Framework for Android. In 32nd Annual Network and Distributed System Security Symposium, NDSS (pp. 24-28).
Auer, M., Arcuschin Moreno, I., & Fraser, G. (2024, April). Wallmauer: Robust code coverage instrumentation for android apps. In Proceedings of the 5th ACM/IEEE International Conference on Automation of Software Test (AST 2024) (pp. 34-44). https://doi.org/10.1145/3644032.3644462
Azim, T., & Neamtiu, I. (2013, October). Targeted and depth-first exploration for systematic testing of android apps. In Proceedings of the 2013 ACM SIGPLAN international conference on Object oriented programming systems languages & applications (pp. 641-660). https://doi.org/10.1145/2509136.2509549
Cobetura. (2025). Retrieved from https://sourceforge.net/projects/cobertura/
Dashevskyi, S., Gadyatskaya, O., Pilgun, A., & Zhauniarovich, Y. (2018, October). The influence of code coverage metrics on automated testing efficiency in android. In Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security (pp. 2216-2218). https://doi.org/10.1145/3243734.3278524
Eke, N. O., Salihu, I. A., & Usman, A. (2023, November). Comparative Analysis of Fully Automated Testing Techniques for Android Applications. In 2023 2nd International Conference on Multidisciplinary Engineering and Applied Science (ICMEAS) (pp. 1-6). IEEE. DOI: 10.1109/ICMEAS58693.2023.10429901
EMMA: a free Java code coverage tool. (2025). Retrieved from https://emma.sourceforge.net/Horváth, F., Gergely, T., Beszédes, Á., Tengeri, D., Balogh, G., & Gyimóthy, T. (2019). Code coverage differences of Java bytecode and source code instrumentation tools. Software Quality Journal, 27, 79-123.
Huang, C. Y., Chiu, C. H., Lin, C. H., & Tzeng, H. W. (2015, June). Code coverage measurement for Android dynamic analysis tools. In 2015 IEEE International Conference on Mobile Services (pp. 209-216). IEEE. DOI: 10.1109/MobServ.2015.38
Jacoco. (2025). Retrieved from https://www.eclemma.org/jacoco/
Liu, J., Wu, T., Deng, X., Yan, J., & Zhang, J. (2017, February). InsDal: A safe and extensible instrumentation tool on Dalvik byte-code for Android applications. In 2017 IEEE 24th international conference on software analysis, evolution and reengineering (SANER) (pp. 502-506). IEEE. DOI: 10.1109/SANER.2017.7884662
Memon, A. M., Soffa, M. L., & Pollack, M. E. (2001, September). Coverage criteria for GUI testing. In Proceedings of the 8th European software engineering conference held jointly with 9th ACM SIGSOFT international symposium on Foundations of software engineering (pp. 256-267). https://doi.org/10.1145/503209.503244
Muazu, A. A., Hashim, A. S., Audi, U. I. I., & Maiwada, U. D. (2024). Refining a one-parameter-at-a-time approach using harmony search for optimizing test suite size in combinatorial t-way testing. IEEE Access. DOI: 10.1109/ACCESS.2024.3463953
Pathy, S., Panda, S., & Baboo, S. A. R. A. D. A. (2015). A review on code coverage analysis. International Journal of Computer Science & Engineering Technology (IJCSET), 6(10), 580-587.
Pilgun, A., Gadyatskaya, O., Dashevskyi, S., Zhauniarovich, Y., & Kushniarou, A. (2018, October). An effective android code coverage tool. In Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security (pp. 2189-2191). https://doi.org/10.1145/3243734.3278484
Pilgun, A., Gadyatskaya, O., Zhauniarovich, Y., Dashevskyi, S., Kushniarou, A., & Mauw, S. (2020). Fine-grained code coverage measurement in automated black-box android testing. ACM Transactions on Software Engineering and Methodology (TOSEM), 29(4), 1-35. https://doi.org/10.1145/3395042
Romdhana, A., Ceccato, M., Georgiu, G. C., Merlo, A., & Tonella, P. (2021, April). Cosmo: Code coverage made easier for android. In 2021 14th IEEE conference on software testing, verification and validation (ICST) (pp. 417-423). IEEE. DOI: 10.1109/ICST49551.2021.00053
Salihu, I. A., Usman, A. U., Eke, N. O., Ibrahim, R., & Kusharki, M. B. (2023, November). Mutation Testing Techniques for Android Applications: A Comparative Study. In 2023 2nd International Conference on Multidisciplinary Engineering and Applied Science (ICMEAS) (Vol. 1, pp. 1-5). IEEE. DOI: 10.1109/ICMEAS58693.2023.10429866
Salihu, I. A., & Ibrahim, R. (2016, November). Systematic exploration of android apps' events for automated testing. In Proceedings of the 14th International Conference on Advances in Mobile Computing and Multi Media (pp. 50-54). https://doi.org/10.1145/3007120.3011072
Samhi, J., & Zeller, A. (2024, July). AndroLog: Android Instrumentation and Code Coverage Analysis. In Companion Proceedings of the 32nd ACM International Conference on the Foundations of Software Engineering (pp. 597-601). https://doi.org/10.1145/3663529.3663806
Salihu, I. A., Ibrahim, R., & Usman, A. (2018, August). A Static-dynamic Approach for UI Model Generation for Mobile Applications. In 2018 7th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions)(ICRITO) (pp. 96-100). IEEE. DOI: 10.1109/ICRITO.2018.8748410
Shahid, M., Ibrahim, S., & Mahrin, M. N. R. (2011). A study on test coverage in software testing. Advanced Informatics School (AIS), Universiti Teknologi Malaysia, International Campus, Jalan Semarak, Kuala Lumpur, Malaysia, 1.
Shelke, S., & Nagpure, S. (2014). The Study of various code coverage tools. International Journal of Computer Trends and Technology (IJCTT), 13(1).
Usman, A., Boukar, M. M., Suleiman, M. A., & Salihu, I. A. (2024). Test Case Generation Approach for Android Applications using Reinforcement Learning. Engineering, Technology & Applied Science Research, 14(4), 15127-15132. https://doi.org/10.48084/etasr.7422.Z
Usman, A., Ibrahim, N., & Salihu, I. A. (2018, February). Test case generation from android mobile applications focusing on context events. In Proceedings of the 2018 7th international conference on software and computer applications (pp. 25-30). https://doi.org/10.1145/3185089.3185099
Usman, A., Ibrahim, N., & Salihu, I. A. (2020). TEGDroid: Test case generation approach for android apps considering context and GUI events. International Journal on Advanced Science, Engineering and Information Technology, 10(1), 16.
Usman, A., Ibrahim, R., Sulaiman, M. A., & Salihu, I. A. (2024). An in-depth analysis of machine learning based techniques for automated testing of android applications. International Journal of Communication Networks and Information Security, 16(3), 663-683.
Usman, A., Boukar, M. M., Suleiman, M. A., Salihu, I. A., & Eke, N. O. (2023). Reinforcement learning for testing android applications: A review. In 2023 2nd International Conference on Multidisciplinary Engineering and Applied Science (ICMEAS) (Vol. 1, pp. 1-6). IEEE.
Yang, Q., Li, J. J., & Weiss, D. (2006, May). A survey of coverage-based testing tools. In Proceedings of the 2006 international workshop on Automation of software test (pp. 99-103). https://doi.org/10.1145/1138929.1138949
Yang, S., Huang, S., & Hui, Z. (2019). Theoretical Analysis and Empirical Evaluation of Coverage Indictors for Closed Source APP Testing. IEEE Access, 7, 162323-162332.
Yeh, C. C., & Huang, S. K. (2015, July). Covdroid: A black-box testing coverage system for android. In 2015 IEEE 39th annual computer software and applications conference (Vol. 3, pp. 447-452). IEEE. DOI: 10.1109/COMPSAC.2015.125
Zhauniarovich, Y., Philippov, A., Gadyatskaya, O., Crispo, B., & Massacci, F. (2015, August). Towards black box testing of android apps. In 2015 10th International Conference on Availability, Reliability and Security (pp. 501-510). IEEE. DOI: 10.1109/ARES.2015.70
PDF