Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

5-2017

Abstract

Program assertions are useful for many program analysis tasks. They are however often missing in practice. In this work, we develop a novel approach for generating likely assertions automatically based on active learning. Our target is complex Java programs which cannot be symbolically executed (yet). Our key idea is to generate candidate assertions based on test cases and then apply active learning techniques to iteratively improve them. The experiments show that active learning really helps to improve the generated assertions.

Keywords

Active learning, Assertion generation, Testing

Discipline

Software Engineering

Research Areas

Software and Cyber-Physical Systems

Publication

ICSE '17: Proceedings of the 39th IEEE/ACM International Conference on Software Engineering: Buenos Aires, Argentina, May 20-28

First Page

155

Last Page

157

ISBN

9781538615898

Identifier

10.1109/ICSE-C.2017.87

Publisher

IEEE Computer Society

City or Country

Los Alamitos, CA

Additional URL

https://doi.org/10.1109/ICSE-C.2017.87

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