Supporting comprehension of unfamiliar programs by modeling an expert's perception

Developers need to understand many Software Engineering (SE) artifacts while making changes to the code. In such cases, developers use cues extensively to establish relevance of an information with the task. Their familiarity with different kind of cues will help them in comprehending a program. But, developers face information overload because (a) there are many cues and (b) they might be unfamiliar with artifacts. So, we propose a novel approach to overcome information overload problem by modeling developer's perceived value of information based on cues. In this preliminary study, we validate one such model for common comprehension tasks. We also apply this model to summarize source code. An evaluation of the generated summaries resulted in 83% similarity with summaries recorded by developers. The promising results encourages us to create a repository of perception models that can later aid complex SE tasks.