Campus Units

Computer Science

Document Type

Conference Proceeding

Conference

The 37th International Conference on Software Engineering (ICSE '15)

Publication Version

Accepted Manuscript

Link to Published Version

https://dx.doi.org/10.1109/ICSE.2015.339

Publication Date

2015

Journal or Book Title

Proceedings of the 37th International Conference on Software Engineering (ICSE '15)

Volume

2

First Page

579

Last Page

582

DOI

10.1109/ICSE.2015.339

Conference Date

May 16-24, 2015

City

Florence, Italy

Abstract

Despite their proven benefits, useful, comprehensible, and efficiently checkable specifications are not widely available. This is primarily because writing useful, non-trivial specifications from scratch is too hard, time consuming, and requires expertise that is not broadly available. Furthermore, the lack of specifications for widely-used libraries and frameworks, caused by the high cost of writing specifications, tends to have a snowball effect. Core libraries lack specifications, which makes specifying applications that use them expensive. To contain the skyrocketing development and maintenance costs of high assurance systems, this self-perpetuating cycle must be broken. The labor cost of specifying programs can be significantly decreased via advances in specification inference and synthesis, and this has been attempted several times, but with limited success. We believe that practical specification inference and synthesis is an idea whose time has come. Fundamental breakthroughs in this area can be achieved by leveraging the collective intelligence available in software artifacts from millions of open source projects. Finegrained access to such data sets has been unprecedented, but is now easily available. We identify research directions and report our preliminary results on advances in specification inference that can be had by using such data sets to infer specifications.

Comments

This article is published as Rajan, Hridesh, Tien N. Nguyen, Gary T. Leavens, and Robert Dyer. "Inferring behavioral specifications from large-scale repositories by leveraging collective intelligence." In Proceedings of the 37th International Conference on Software Engineering-Volume 2, pp. 579-582. IEEE Press, 2015. doi: 10.1109/ICSE.2015.339. Posted with permission.

Rights

© 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Copyright Owner

IEEE

Language

en

File Format

application/pdf

Published Version

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