PhD Candidate
Massachusetts Institute of Technology
Areas of Interest
- Programming Systems
- Database Management Systems
Poster
Using Active Learning to Synthesize Models of Applications that Access Databases
Abstract
We present Konure, a new system that uses active learning to infer models of applications that access relational databases. Konure comprises a domain-specific language (each model is a program in this language) and associated inference algorithm that infers models of applications whose behavior can be expressed in this language. The inference algorithm generates inputs and database configurations, runs the application, then observes the resulting database traffic and outputs to progressively refine its current model hypothesis. Because the technique works with only externally observable inputs, outputs, and database configurations, it can infer the behavior of applications written in arbitrary languages using arbitrary coding styles (as long as the behavior of the application is expressible in the domain-specific language). Konure also implements a regenerator that produces a translated Python implementation of the application that systematically includes relevant security and error checks.
Bio
Jiasi Shen is a PhD student advised by professor Martin Rinard at MIT. She received her bachelor's degree from Peking University. Her research interests are in programming languages and software engineering.
