Automatic generation of function block applications using evolutionary algorithms: Initial explorations

Mironovich, Vladimir; Buzdalov, Maxim; Vyatkin, Valeriy

doi:10.1109/indin.2017.8104858

Cited by 5 publications

(2 citation statements)

References 15 publications

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“…This process is repeated until a satisfactory solution is found. EAs benefits: they can be used to: generate code that is efficient and effective [37], easy to maintain [38], for different programming languages, platforms, and applications [37].…”

Section: Evolutionary Algorithms (Eas)mentioning

confidence: 99%

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A Comparative Review of AI Techniques for Automated Code Generation in Software Development: Advancements, Challenges, and Future Directions

Odeh,

Mohammed

2024

TEM Journal

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Artificial Intelligence (AI), as one of the most important fields of computer science, plays a significant role in the software development life cycle process, especially in the implementation phase, where developers require considerable effort to convert software requirements and design into code. Automated Code Generation (ACG) using AI can help in this phase. Automating the code generation process is becoming increasingly popular as a solution to address various software development challenges and increase productivity. In this work, we provide a comprehensive review and discussion of traditional and AI techniques used for ACG, their challenges, and limitations. By analysing a selection of related studies, we will identify all AI methods and algorithms used for ACG, extracting the evaluation metrics and criteria such as Accuracy, Efficiency, Scalability, Correctness, Generalization, and more. These criteria will be used to perform a comparative result for AI methods used for ACG, exploring their applications, strengths, weaknesses, performance, and future applications.

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Section: Evolutionary Algorithms (Eas)mentioning

confidence: 99%

“…Code Generation using EAs Explore the application of evolutionary algorithms in automating code generation [37], [48], [49]. This research direction could involve investigating how evolutionary algorithms can be used to generate optimized code and solve complex programming problems.…”

Section: For Big Code and Naturalnessmentioning

confidence: 99%