Performance is one of the key aspects of non-functional qualities, where performance bugs can cause significant performance degradation and lead to poor user experience.
Our empirical evaluation suggests that our
approach can learn useful API usage models which can provide
recommendations with higher levels of accuracy than the baseline
n-gram model.
Closest to our work, is the series of work on bug report severity prediction by Menzies and Marcus [16], Lamkanfi et al. [13], [14], and our own previous work [27].