Review and Mapping of Search-Based Approaches for Program Synthesis

Context: Program synthesis tools reduce software development costs by generating programs that perform tasks depicted by some specifications. Various methodologies have emerged for program synthesis, among which search-based algorithms have shown promising results. However, the proliferation of sear...

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Veröffentlicht in:Information (Basel) Jg. 16; H. 5; S. 401
Hauptverfasser: Saber, Takfarinas, Tao, Ning
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Basel MDPI AG 01.05.2025
Schlagworte:
Algorithms
Artificial intelligence
automated programming
Automation
Digital libraries
Efficiency
heuristic
Large language models
Literature reviews
Machine learning
Mapping
metaheuristic
Natural language
Polls & surveys
program synthesis
Representations
Search algorithms
search-based algorithm
Software
Software development
Software engineering
survey
Syntax
Synthesis
Germany
ISSN:2078-2489, 2078-2489
Online-Zugang:Volltext
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Zusammenfassung:Context: Program synthesis tools reduce software development costs by generating programs that perform tasks depicted by some specifications. Various methodologies have emerged for program synthesis, among which search-based algorithms have shown promising results. However, the proliferation of search-based program synthesis tools utilising diverse search algorithms and input types and targeting various programming tasks can overwhelm users seeking the most suitable tool. Objective: This paper contributes to the ongoing discourse by presenting a comprehensive review of search-based approaches employed for program synthesis. We aim to offer an understanding of the guiding principles of current methodologies by mapping them to the required type of user intent, the type of search algorithm, and the representation of the search space. Furthermore, we aim to map the diverse search algorithms to the type of code generation tasks in which they have shown success, which would serve as a guideline for applying search-based approaches for program synthesis. Method: We conducted a literature review of 67 academic papers on search-based program synthesis. Results: Through analysis, we identified and categorised the main techniques with their trends. We have also mapped and shed light on patterns connecting the problem, the representation and the search algorithm type. Conclusions: Our study summarises the field of search-based program synthesis and provides an entry point to the acumen and expertise of the search-based community on program synthesis.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ObjectType-Literature Review-2
ISSN:2078-2489
2078-2489
DOI:10.3390/info16050401