Prof. Miryung Kim Awarded Computer and Communication Foundations Grant from National Science Foundation
UT ECE Professor Miryung Kim has been awarded a Division of Computer and Communication Foundations EAGER Award from the National Science Foundation for her research on "Information Needs about Software Modification during Collaborative Development Tasks."
The Division of Computing and Communication Foundations (CCF) supports research and education projects that explore the foundations of computing and communication devices and their usage. The Division seeks advances in computing and communication theory, algorithms for computer and computational sciences, and architecture and design of computers and software. CCF-supported projects also investigate revolutionary computing models and technologies based on emerging scientific ideas and integrate research and education activities to prepare future generations of computer science and engineering workers.
Professor Kim's research has two hypotheses about software engineers' information needs during code reviews. The first hypothesis is that different roles in code review, such as an author and a reviewer, lead to different information needs in terms of abstraction levels; thus, existing static and dynamic program analysis that do not distinguish the role of information producer (code author) and consumer (code reviewer) may not be effective in supporting peer reviews. The second hypothesis is that existing communication, awareness, and management support features in collaborative development tools such as an instant messenger, email, and work-flow management provide high-level, yet shallow information, as these tools lack in the ability to provide code-centric information. In order to test these hypotheses, Professor Kim will use several empirical study methods, including focus groups, semi-structured interviews, case studies, and surveys, to acquire comprehensive and systematic understanding of engineers' information needs during peer code reviews.
The outcome of this study will guide the construction of innovative software analyses that can satisfy programmers? information needs, improving the effectiveness of peer code review tasks, ultimately improving programmer productivity and software quality. Furthermore, this study will serve as a basis for identifying what types of information at which abstraction level can best support developers in examining software modification. The findings from this study will also contribute to developing necessary program delta representations, inference algorithms, and infrastructures that will enable engineers to reason about software modification at a high level.
