MUBench: A Benchmark for API-misuse Detectors
| Title | MUBench: A Benchmark for API-misuse Detectors |
| Publication Type | Conference Paper |
| Year of Publication | 2016 |
| Authors | Amani, Sven, Nadi, Sarah, Nguyen, Hoan A., Nguyen, Tien N., Mezini, Mira |
| Conference Name | Proceedings of the 13th International Conference on Mining Software Repositories |
| Publisher | ACM |
| Conference Location | New York, NY, USA |
| ISBN Number | 978-1-4503-4186-8 |
| Keywords | API, 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. |
| URL | https://dl.acm.org/doi/10.1145/2901739.2903506 |
| DOI | 10.1145/2901739.2903506 |
| Citation Key | amani_mubench:_2016 |