Toward Imitating Visual Attention of Experts in Software Development Tasks
This addresses the problem of incorporating expert expertise into intelligent systems for software developers, but it is incremental as it focuses on a conceptual framework without implementation.
The paper proposes a conceptual framework using imitation learning to mimic expert programmers' visual attention from eye movements for software development tasks like issue localization and code generation, but does not present concrete results or numbers.
Expert programmers' eye-movements during source code reading are valuable sources that are considered to be associated with their domain expertise. We advocate a vision of new intelligent systems incorporating expertise of experts for software development tasks, such as issue localization, comment generation, and code generation. We present a conceptual framework of neural autonomous agents based on imitation learning (IL), which enables agents to mimic the visual attention of an expert via his/her eye movement. In this framework, an autonomous agent is constructed as a context-based attention model that consists of encoder/decoder network and trained with state-action sequences generated by an experts' demonstration. Challenges to implement an IL-based autonomous agent specialized for software development task are discussed in this paper.