Accepted article in the journal "Automated Software Engineering" published by Springer-Verlag
Our article "Guided Pattern Mining for API Misuse Detection by Change-Based Code Analysis" by Sebastian Nielebock, Robert Heumüller, Kevin Michael Schott and Frank Ortmeier has been accepted for publication in the journal Fachjournal "Automated Software Engineering“ published by Springer-Verlag.
In this article, we address the problem of API abuse, which occurs when developers incorrectly use the application programming interface of a particular code library. Existing detection tools use pattern mining techniques, i.e. they collect a set of potentially correct API applications and derive common usage patterns as correct specifications. In this way, violations of these specifications can be identified as API abuse. In this work, we analyzed the effects of different prior filtering and search strategies to obtain source code for the pattern mining step and were able to show that certain strategies improve pattern mining and misuse detection results regardless of the mining and detection technique applied.
A preprint of the article can be found on arXiv.