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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MDPI AG
2025-05-01
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| Online Access: | https://www.mdpi.com/2078-2489/16/5/401 |
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| author | Takfarinas Saber Ning Tao |
| author_facet | Takfarinas Saber Ning Tao |
| author_sort | Takfarinas Saber |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-f779c2db47b04cfc93acc59c28d9bf4e |
| institution | Kabale University |
| issn | 2078-2489 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Information |
| spelling | doaj-art-f779c2db47b04cfc93acc59c28d9bf4e2025-08-20T03:47:58ZengMDPI AGInformation2078-24892025-05-0116540110.3390/info16050401Review and Mapping of Search-Based Approaches for Program SynthesisTakfarinas Saber0Ning Tao1Lero the Research Ireland Centre for Software, School of Computer Science, University of Galway, H91 TK33 Galway, IrelandSchool of Computer Science, University College Dublin, D04 C1P1 Dublin, IrelandContext: 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.https://www.mdpi.com/2078-2489/16/5/401program synthesisautomated programmingsearch-based algorithmheuristicmetaheuristicsurvey |
| spellingShingle | Takfarinas Saber Ning Tao Review and Mapping of Search-Based Approaches for Program Synthesis Information program synthesis automated programming search-based algorithm heuristic metaheuristic survey |
| title | Review and Mapping of Search-Based Approaches for Program Synthesis |
| title_full | Review and Mapping of Search-Based Approaches for Program Synthesis |
| title_fullStr | Review and Mapping of Search-Based Approaches for Program Synthesis |
| title_full_unstemmed | Review and Mapping of Search-Based Approaches for Program Synthesis |
| title_short | Review and Mapping of Search-Based Approaches for Program Synthesis |
| title_sort | review and mapping of search based approaches for program synthesis |
| topic | program synthesis automated programming search-based algorithm heuristic metaheuristic survey |
| url | https://www.mdpi.com/2078-2489/16/5/401 |
| work_keys_str_mv | AT takfarinassaber reviewandmappingofsearchbasedapproachesforprogramsynthesis AT ningtao reviewandmappingofsearchbasedapproachesforprogramsynthesis |