Symbolic Automata for Static Specification Mining

In a world where programming is largely based on using APIs, semantic code search emerges as a way to effectively learn how such APIs should be used. Towards this end, we present a formal framework for static specification mining that is able to handle code snippets and incomplete programs. Our framework analyzes code snippets and extract partial temporal specifications. Technically, partial temporal specifications are represented as symbolic automata – automata where transitions may be labeled by variables, and a variable can be substituted by a letter, a word, or a regular language. With the help of symbolic automata, the use of the API is extracted from each snippet of code, and the many separate examples are consolidated to create a fuller usage scenario database that can be queried. We have implemented our approach in a tool called PRIME and applied it to analyze and consolidate thousands of snippets per tested API.

This talk is based on work with Alon Mishne, Sharon Shoham, Eran Yahav, and Hongseok Yang.

Speaker Details

Hila Peleg is a graduate student in the Computer Science department of Tel Aviv University, advised by Eran Yahav and Mooly Sagiv. She also holds a degree in literature. She is currently researching the mining of temporal specifications from large codebases.

Series:
Microsoft Research Talks
Date:
Speakers:
Hila Peleg
Affiliation:
Tel Aviv University

Series: Microsoft Research Talks