Visible to the public MUBench: A Benchmark for API-misuse Detectors

TitleMUBench: A Benchmark for API-misuse Detectors
Publication TypeConference Paper
Year of Publication2016
AuthorsAmani, Sven, Nadi, Sarah, Nguyen, Hoan A., Nguyen, Tien N., Mezini, Mira
Conference NameProceedings of the 13th International Conference on Mining Software Repositories
PublisherACM
Conference LocationNew York, NY, USA
ISBN Number978-1-4503-4186-8
KeywordsAPI, API-misuse detection, APIs, applications programming interfaces, benchmark, bug detection, compositionality, pubcrawl, Resiliency
Abstract

Over the last few years, researchers proposed a multitude of automated bug-detection approaches that mine a class of bugs that we call API misuses. Evaluations on a variety of software products show both the omnipresence of such misuses and the ability of the approaches to detect them. This work presents MuBench, a dataset of 89 API misuses that we collected from 33 real-world projects and a survey. With the dataset we empirically analyze the prevalence of API misuses compared to other types of bugs, finding that they are rare, but almost always cause crashes. Furthermore, we discuss how to use it to benchmark and compare API-misuse detectors.

URLhttp://doi.acm.org/10.1145/2901739.2903506
DOI10.1145/2901739.2903506
Citation Keyamani_mubench:_2016