Speaker: JIASI SHEN, MASSACHUSETTS INSTITUTE OF TECHNOLOGY
Topic: ACTIVE LEARNING FOR SOFTWARE REJUVENATION
Date: THURSDAY, MARCH 31, 2022
Time: 10:00 am – 11:00 am
Zoom: https://uwaterloo.zoom.us/j/99064352856?pwd=cVV0VUlqSEtNNEZFY0lvTk5KVVVpUT09
Meeting ID: 990 6435 2856
Passcode: 193870
Abstract:
Software now plays a central role in numerous aspects of human society. Current software development practices involve significant developer effort in all phases of the software life cycle, including the development of new software, detection and elimination of defects and security vulnerabilities in existing software, maintenance of legacy software, and integration of existing software into more contexts, with the quality of the resulting software still leaving much to be desired. The goal of my research is to improve software quality and reduce costs by automating tasks that currently require substantial manual engineering effort.
I present a novel approach for automatic software rejuvenation, which takes an existing program, learns its core functionality as a black box, builds a model that captures this functionality, and uses the model to generate a new program. The new program delivers the same core functionality but is potentially augmented or transformed to operate successfully in different environments. This research enables the rejuvenation and retargeting of existing software and provides a powerful way for developers to express program functionality that adapts flexibly to a variety of contexts. In this talk, I will show how we applied these techniques to two classes of software systems, specifically database-backed programs and stream-processing computations, and discuss the broader implications of these approaches.
Biography:
Jiasi Shen is a Ph.D. candidate at MIT EECS advised by professor Martin Rinard. She received her bachelor's degree from Peking University. Her main research interests are in programming languages and software engineering. She was named an EECS Rising Star in 2020.
All are welcome!