Statistical language modeling techniques have successfully been applied to large source
code corpora, yielding a variety of new software development tools, such as tools for code …

This paper presents a novel yet intuitive approach to unsupervised feature learning. Inspired
by the human visual system, we explore whether low-level motion-based grouping cues can …

Predicting function names in stripped binaries is an extremely useful but challenging task, as
it requires summarizing the execution behavior and semantics of the function in human …

Locating bugs is important, difficult, and expensive, particularly for large-scale systems. To
address this, natural language information retrieval techniques are increasingly being used …

When a new bug report is received, developers usually need to reproduce the bug and
perform code reviews to find the cause, a process that can be tedious and time consuming …

Studies have shown that good comments can help programmers quickly understand what a
method does, aiding program comprehension and software maintenance. Unfortunately, few …

The n-gram language model, which has its roots in statistical natural language processing,
has been shown to successfully capture the repetitive and predictable regularities …

From the standpoint of retrieval from large software libraries for the purpose of bug
localization, we compare five generic text models and certain composite variations thereof …

Recent findings suggest that Information Retrieval (IR)-based bug localization techniques do
not perform well if the bug report lacks rich structured information (eg, relevant program …

Program understanding plays a pivotal role in software maintenance and evolution: a deep
understanding of code is the stepping stone for most software-related activities, such as bug …