Recent Trends in Programming languages
Volume 13, Issue 2 (2026)
Table of contents
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AI-Native Programming Languages: Reconsidering Programming Language Selection in the Era of Generative AI and Autonomous Coding
Abstract: The role of programming languages is undergoing a significant transformation as generative artificial intelligence becomes integrated into everyday software development. Programming is gradually moving from an activity dominated by manual source code production toward a collaborative environment in which developers work with large language models, intelligent coding assistants, automated testing systems, and increasingly autonomous software agents. This transformation introduces a new dimension to programming language selection. Historically, programming languages have …
Published in Recent Trends in Programming languages · Vol. 13, Issue 2, 2026 · pp. 1–16 Read article
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Bug Tracking and Resolution System: A Rule-Based and Python-Driven Approach
Abstract: The way things operate and how they will age from a performance and user interaction standpoint, what types of loads they can handle, and how maintenance will be needed in the future are all connected to how working out glitches affects the future and how it feels to the users. Many older systems record problems, track the steps taken to resolve them, and provide very little in the way of …
Published in Recent Trends in Programming languages · Vol. 13, Issue 2, 2026 · pp. 17–27 Read article
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LLM-Assisted Programming: Trends, Evaluation Gaps, and Software Assurance
Abstract: Large language models (LLMs) are increasingly used for code generation, software testing, program repair, and security analysis. However, their evaluation still relies heavily on functional benchmarks that often focus on small, isolated programming tasks. Such benchmarks provide limited insight into security, test quality, repository-level dependencies, and maintainability. This study examines how the evaluation of LLM-assisted programming has developed across these application areas. The literature shows a gradual shift from function-level …
Published in Recent Trends in Programming languages · Vol. 13, Issue 2, 2026 · pp. 28–42 Read article
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AI-Assisted Programming, Memory Safety, Multi-Paradigm Design and Emerging Development Models
Abstract: As the field of artificial intelligence (AI) continues to evolve at a fast pace, and specifically with the rise of large language models (LLMs), the software design, implementation, testing, and maintenance landscape has undergone unprecedented transformation. Although programming languages are still the main language for writing computational logic, the way developers interact with programming languages is now increasingly mediated by AI-based tools. Current AI coding systems can help with code …
Published in Recent Trends in Programming languages · Vol. 13, Issue 2, 2026 · pp. 43–50 Read article
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Programming Languages for Robotics: A Comprehensive Review of Applications, Features, and System Integration
Abstract: The rapid advancement of industrial automation, artificial intelligence, and autonomous systems has increased the importance of effective programming approaches for modern robotic applications. Robot programming languages provide the computational foundation for controlling robotic motion, interacting with sensors and actuators, implementing autonomous operations, and developing simulation-based solutions. This paper presents a comparative review of major programming languages used in robotics, with particular emphasis on C/C++, Python, Java, C#/.NET, and MATLAB. The …
Published in Recent Trends in Programming languages · Vol. 13, Issue 2, 2026 · pp. 51–62 Read article