Genetic synthesis of concurrent code using model checking and statistical model checking

Lei Bu, Doron Peled, Dachuan Shen, Yuan Zhuang

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

2 Scopus citations


Genetic programming (GP) is a heuristic method for automatically generating code. It applies probabilistic-based generation and mutation of code, combined with “natural selection” principles, using a fitness function. Often, the fitness is calculated based on a large test suite. Recently, GP was applied for synthesizing correct-by-design concurrent code from temporal specification, where model checking was used for calculating the fitness function. A deficiency of this approach is that it uses a limited number of fitness values, based on a small number of modes for each verified specification property (e.g., satisfies, does not satisfy a given property). Furthermore, the need to apply model checking on many candidate solutions using the genetic process makes using an off-the-shelf model checker such as Spin prohibitively expensive. The repeated invocation of such a tool, compiling the code for a new candidate solution and running it, can render the performance of this approach several orders of magnitude slower than using an internal model checking. To tackle this problem, we describe here the use of a combination of statistical model checking, and a light use of model checking, for calculating the fitness required by GP.

Original languageEnglish
Title of host publicationModel Checking Software - 25th International Symposium, SPIN 2018, Proceedings
EditorsMaría del Gallardo, Pedro Merino
PublisherSpringer Verlag
Number of pages17
ISBN (Print)9783319941103
StatePublished - 2018
Event25th International Symposium on Model Checking Software, SPIN 2018 - Málaga, Spain
Duration: 20 Jun 201822 Jun 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10869 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference25th International Symposium on Model Checking Software, SPIN 2018

Bibliographical note

Publisher Copyright:
© 2018, Springer International Publishing AG, part of Springer Nature.


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