MCGP: A software synthesis tool based on model checking and genetic programming

Gal Katz, Doron Peled

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

8 Scopus citations

Abstract

We present MCGP - a tool for generating and correcting code, based on our synthesis approach combining deep Model Checking and Genetic Programming. Given an LTL specification, genetic programming is used for generating new candidate solutions, while deep model checking is used for calculating to what extent (i.e., not only whether) a candidate solution program satisfies a property. The main challenge is to construct from the result of the deep model checking a fitness function that has a good correlation with the distance of the candidate program from a correct solution. The tool allows the user to control various parameters, such as the syntactic building blocks, the structure of the programs, and the fitness function, and to follow their effect on the convergence of the synthesis process.

Original languageEnglish
Title of host publicationAutomated Technology for Verification and Analysis - 8th International Symposium, ATVA 2010, Proceedings
Pages359-364
Number of pages6
DOIs
StatePublished - 2010
Event8th International Symposium on Automated Technology for Verification and Analysis, ATVA 2010 - Singapore, Singapore
Duration: 21 Sep 201024 Sep 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6252 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference8th International Symposium on Automated Technology for Verification and Analysis, ATVA 2010
Country/TerritorySingapore
CitySingapore
Period21/09/1024/09/10

Bibliographical note

Funding Information:
This research was supported in part by ISF Science Foundation grant 1262/09.

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