Computer Science > Software Engineering
arXiv:2306.00521 (cs)
[Submitted on 1 Jun 2023 (v1), last revised 4 Jun 2023 (this version, v2)]
Title:Genetic Algorithms for Searching a Matrix of Metagrammars for Synthesis
View a PDF of the paper titled Genetic Algorithms for Searching a Matrix of Metagrammars for Synthesis, by Yixuan Li and 3 other authors
View PDFAbstract:Syntax-guided synthesis is a paradigm in program synthesis in which the search space of candidate solutions is constrained by a syntactic template in the form of a grammar. These syntactic constraints serve two purposes: constraining the language to the space the user desires, but also rendering the search space tractable for the synthesizer. Given a well-written syntactic template, this is an extremely effective technique. However, this is highly dependent on the user providing such a template: a syntactic template that is too large results in a larger search space and slower synthesis, and a syntactic template that is too small may not contain the solution needed. In this work, we frame the space of syntactic templates as a matrix of rules, and demonstrate how this matrix can be searched effectively with little training data using simple search techniques such as genetic algorithms, giving improvements in both the number of benchmarks solved and solving time for the state-of-the-art synthesis solver.
| Comments: | SYNT 2023 of CAV 2023, 4 Pages |
| Subjects: | Software Engineering (cs.SE); Programming Languages (cs.PL) |
| Cite as: | arXiv:2306.00521 [cs.SE] |
| (orarXiv:2306.00521v2 [cs.SE] for this version) | |
| https://doi.org/10.48550/arXiv.2306.00521 arXiv-issued DOI via DataCite |
Submission history
From: Yixuan Li [view email][v1] Thu, 1 Jun 2023 10:22:22 UTC (110 KB)
[v2] Sun, 4 Jun 2023 11:46:42 UTC (110 KB)
Full-text links:
Access Paper:
- View PDF
- Other Formats
View a PDF of the paper titled Genetic Algorithms for Searching a Matrix of Metagrammars for Synthesis, by Yixuan Li and 3 other authors
References & Citations
Bookmark
Bibliographic and Citation Tools
Bibliographic Explorer(What is the Explorer?)
Connected Papers(What is Connected Papers?)
Litmaps(What is Litmaps?)
scite Smart Citations(What are Smart Citations?)
Code, Data and Media Associated with this Article
alphaXiv(What is alphaXiv?)
CatalyzeX Code Finder for Papers(What is CatalyzeX?)
DagsHub(What is DagsHub?)
Gotit.pub(What is GotitPub?)
Hugging Face(What is Huggingface?)
Papers with Code(What is Papers with Code?)
ScienceCast(What is ScienceCast?)
Demos
Recommenders and Search Tools
Influence Flower(What are Influence Flowers?)
CORE Recommender(What is CORE?)
arXivLabs: experimental projects with community collaborators
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.
Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.
Have an idea for a project that will add value for arXiv's community?Learn more about arXivLabs.