Home > Research > Publications & Outputs > MUBench

Links

Text available via DOI:

View graph of relations

MUBench: a benchmark for API-misuse detectors

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Published
Close
Publication date2016
Host publicationMSR '16 Proceedings of the 13th International Conference on Mining Software Repositories
Place of PublicationNew York
PublisherACM
Pages464-467
Number of pages4
ISBN (print)9781450341868
<mark>Original language</mark>English

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.