Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

11-2018

Abstract

In 2007, the Deckard paper was published at ICSE. Since its publication, it has led to much follow-up research and applications. The paper made two core contributions: a novel vector embedding of structured code for fast similarity detection, and an application of the embedding for clone detection, resulting in the Deckard tool. The vector embedding is simple and easy to adapt. Similar code detection is also fundamental for a range of classical and emerging problems in software engineering, security, and computer science education (e.g., code reuse, refactoring, porting, translation, synthesis, program repair, malware detection, and feedback generation). Both have buttressed the paper’s influence.In 2018, the Deckard paper received the ACM SIGSOFT Impact Paper award. In this keynote, we take the opportunity to review the work’s inception, evolution and impact on its subsequent work and applications, and to share our thoughts on exciting ongoing and future developments.

Keywords

code vectorization, code similarity, code search, code learning

Discipline

Software Engineering

Research Areas

Software and Cyber-Physical Systems

Publication

ESEC/FSE 2018: Proceedings of the 26th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering: Lake Buena Vista, FL, November 4-9

First Page

2

Last Page

2

ISBN

9781450355735

Identifier

10.1145/3236024.3280856

Publisher

ACM

City or Country

New York

Additional URL

https://doi.org/10.1145/3236024.3280856

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