CS Colloquium (BMAC)


speaker Computer Science Department Special Seminar
Human-Centric Tools for Software Maintenance

Speaker: Austin Henley, PhD Candidate, Computer Science Department, University of Memphis

11:00AM ~ 11:50AM, February 26, 2018

Where: CSB130

Abstract:All software failures are fundamentally the fault of humans—either the design was ill-formed or the implementation contained a bug. By designing more human-centric development tools, developers can produce higher quality code in less time with lower cognitive load. In this talk, I will present tools for supporting two common activities in software maintenance: code navigation and code reviewing. Since navigating code is known to be time consuming and problematic, I designed Patchworks, a novel code editor interface that enables efficient juxtaposition and rapid scanning of code. Two empirical studies found that developers using Patchworks navigated faster and made fewer navigation mistakes than with traditional code editors. Once developers have made changes to the code, other developers must review and discuss the changes to ensure the code is of sufficient quality. To aid developers in this tedious task of reviewing code, I designed CFar, an automated code reviewer that provides feedback using program analysis. A laboratory study and field deployment involving 98 developers at Microsoft found that using CFar increased communication, productivity, and review quality.

Bio:Austin Henley is a PhD candidate in the Computer Science department at the University of Memphis. He conducts research in the areas of software engineering and human-computer interaction. In particular, he conducts empirical studies and designs software development tools with the goal of improving developer productivity. He has worked as a research intern at Microsoft Research, National Instruments, and IBM Research. His research has been published in prestigious venues, including CHI and FSE, winning an ACM SIGSOFT Distinguished Paper Award, an IEEE Honorable Mention Award, and an IEEE Best Paper Award.