A Systematic Literature Review of 10 years of Research on Program Synthesis and Natural Language Processing

Program synthesis is the process of automatically generating software from a requirement specification. This paper presents a systematic literature review focused on program synthesis from specifications expressed in natural language. The research problem centers on the complexity of automatically g...

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Vydané v:Programming and computer software Ročník 50; číslo 8; s. 725 - 741
Hlavní autori: Ramírez-Rueda, Rolando, Benítez-Guerrero, Edgard, Mezura-Godoy, Carmen, Bárcenas, Everardo
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Moscow Pleiades Publishing 01.12.2024
Springer Nature B.V
Predmet:
Artificial Intelligence
Automation
Cognition & reasoning
Computer Science
Generative artificial intelligence
Language
Large language models
Literature reviews
Multimedia
Natural language processing
Neural networks
Operating Systems
Requirements specifications
Semantics
Software
Software development
Software Engineering
Software Engineering/Programming and Operating Systems
Speech recognition
Synthesis
Systematic review
Trends
ISSN:0361-7688, 1608-3261
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Shrnutí:Program synthesis is the process of automatically generating software from a requirement specification. This paper presents a systematic literature review focused on program synthesis from specifications expressed in natural language. The research problem centers on the complexity of automatically generating accurate and robust code from high-level, ambiguous natural language descriptions – a barrier that limits the broader adoption of automatic code generation in software development. To address this issue, the study systematically examines research published between 2014 and 2024, focusing on works that explore various approaches to program synthesis from natural language inputs. The review follows a rigorous methodology, incorporating search strings tailored to capture relevant studies from five major data sources: IEEE, ACM, Springer, Elsevier, and MDPI. The selection process applied strict inclusion and exclusion criteria, resulting in a final set of 20 high-quality studies. The findings reveal significant advancements in the field, particularly in the integration of large language models (LLMs) with program synthesis techniques. The review also highlights the challenges and concludes by outlining key trends and proposing future research directions aimed at overcoming these challenges and expanding the applicability of program synthesis across various domains.
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ISSN:0361-7688
1608-3261
DOI:10.1134/S0361768824700737