article

Mining specifications

Authors:

Rastislav Bodík,

James R. LarusAuthors Info & Claims

ACM SIGPLAN Notices, Volume 37, Issue 1

Pages 4 - 16

https://doi.org/10.1145/565816.503275

Published: 01 January 2002 Publication History

Abstract

Program verification is a promising approach to improving program quality, because it can search all possible program executions for specific errors. However, the need to formally describe correct behavior or errors is a major barrier to the widespread adoption of program verification, since programmers historically have been reluctant to write formal specifications. Automating the process of formulating specifications would remove a barrier to program verification and enhance its practicality.This paper describes specification mining, a machine learning approach to discovering formal specifications of the protocols that code must obey when interacting with an application program interface or abstract data type. Starting from the assumption that a working program is well enough debugged to reveal strong hints of correct protocols, our tool infers a specification by observing program execution and concisely summarizing the frequent interaction patterns as state machines that capture both temporal and data dependences. These state machines can be examined by a programmer, to refine the specification and identify errors, and can be utilized by automatic verification tools, to find bugs.Our preliminary experience with the mining tool has been promising. We were able to learn specifications that not only captured the correct protocol, but also discovered serious bugs.

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Published In

cover image ACM SIGPLAN Notices

ACM SIGPLAN Notices Volume 37, Issue 1

Jan. 2002

342 pages

ISSN:0362-1340

EISSN:1558-1160

DOI:10.1145/565816

Issue’s Table of Contents

POPL '02: Proceedings of the 29th ACM SIGPLAN-SIGACT symposium on Principles of programming languages
January 2002
351 pages
ISBN:1581134509
DOI:10.1145/503272
Conference Chair:
John Launchbury
OGI and Galois Connections
,
Program Chair:
John C. Mitchell
Stanford University

Copyright © 2002 ACM.

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Association for Computing Machinery

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Publication History

Published: 01 January 2002

Published in SIGPLAN Volume 37, Issue 1

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https://dl.acm.org/doi/10.1145/3694715.3695974
Germiniani SNicoletti DPravadelli G(2024)Invited Talk: Pros and Cons of Assertion Mining2024 IEEE 25th Latin American Test Symposium (LATS)10.1109/LATS62223.2024.10534611(1-2)Online publication date: 9-Apr-2024
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