Fine-grained Code Coverage Measurement in Automated Black-box Android Testing

Author:

Pilgun Aleksandr1ORCID,Gadyatskaya Olga2,Zhauniarovich Yury3,Dashevskyi Stanislav4,Kushniarou Artsiom5,Mauw Sjouke6

Affiliation:

1. SnT, University of Luxembourg, Luxembourg

2. LIACS, Leiden University, Leiden, Netherlands

3. Independent Researcher, Uzda, Belarus

4. Forescout Technologies, Eindhoven, Netherlands

5. iTechArt Inc., Minsk, Belarus

6. CSC 8 SnT, University of Luxembourg

Abstract

Today, there are millions of third-party Android applications. Some of them are buggy or even malicious. To identify such applications, novel frameworks for automated black-box testing and dynamic analysis are being developed by the Android community. Code coverage is one of the most common metrics for evaluating effectiveness of these frameworks. Furthermore, code coverage is used as a fitness function for guiding evolutionary and fuzzy testing techniques. However, there are no reliable tools for measuring fine-grained code coverage in black-box Android app testing. We present the Android Code coVerage Tool, ACVTool for short, that instruments Android apps and measures code coverage in the black-box setting at class, method and instruction granularity. ACVTool has successfully instrumented 96.9% of apps in our experiments. It introduces a negligible instrumentation time overhead, and its runtime overhead is acceptable for automated testing tools. We demonstrate practical value of ACVTool in a large-scale experiment with Sapienz, a state-of-the-art automated testing tool. Using ACVTool on the same cohort of apps, we have compared different coverage granularities applied by Sapienz in terms of the found amount of crashes. Our results show that none of the applied coverage granularities clearly outperforms others in this aspect.

Funder

Fonds National de la Recherche Luxembourg

Publisher

Association for Computing Machinery (ACM)

Subject

Software

Reference81 articles.

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