A systematic mapping on software testing for blockchains

Abstract The purpose of this study is to identify and classify studies published on software testing techniques applied to blockchain systems. Previously published reviews in related areas have a narrow focus and/or do not follow a systematic review protocol. We conducted a systematic mapping based on an initial selection of 1025 studies. A rigorous selection process resulted in a final pool of 17 primary studies. These studies are categorized with respect to the employed testing methods, considered quality attributes, and functionality. We observe that most of the publications focus on testing functional correctness or security, whereas the testing of runtime performance attracts less attention. Existing approaches mostly employ fuzz testing or mutation testing. Search-based testing is usually combined with these techniques. The application of model-based testing is rare. The adaptability of fuzz testing and model-based testing techniques to changing blockchain platforms and languages remains a concern. On the other hand, performance and scalability issues are noted for search-based techniques and mutation testing. The use and integration of multiple testing techniques also stand out as a viable research direction.