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...

Full description

Saved in:
Bibliographic Details
Main Authors: Takfarinas Saber, Ning Tao
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Information
Subjects:
Online Access:https://www.mdpi.com/2078-2489/16/5/401
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
ISSN:2078-2489