Topic modeling using models such as Latent Dirichlet Allocation (LDA) is a text mining
technique to extract human-readable semantic “topics”(ie, word clusters) from a corpus of …

Automatically localizing software bugs to the changesets that induced them has the potential
to improve software developer efficiency and to positively affect software quality. To facilitate …

This chapter describes traditional and intuitive fault localization techniques, including
program logging, assertions, breakpoints, and profiling. Many advanced fault localization …

Bug localization is the automated process of finding the possible faulty files in a software
project. Bug localization allows developers to concentrate on vital files. Information retrieval …

The automation of an increasingly large number of software engineering tasks is becoming
possible thanks to Machine Learning (ML). One foundational building block in the …

Software specifications often use natural language to describe the desired behavior, but
such specifications are difficult to verify automatically. We present Swami, an automated …

Software systems are frequently affected by a few defects. In general, the developers make
use of the data present in the file, while reporting a bug; thus, they can help to fix the bug by …

Context Bug localization, which locates suspicious snippets related to the bugs mentioned in
the bug reports, is time-consuming and laborious. Many automatic bug localization methods …

Various evaluation datasets are used to evaluate the performance of information retrieval-
based bug localization (IRBL) techniques. To accurately evaluate the IRBL and furthermore …

Context: One of the time-consuming maintenance tasks is the localization of bugs especially
in large software systems. Developers have to follow a tedious process to reproduce the …