Recent Trends in Programming languages · Vol. 13, No. 2 (2026)
Programming in the Age of AI: Recent Trends in Programming Languages 13(2)
By STM Journals ·
This issue of Recent Trends in Programming Languages looks at how programming is changing as AI tools enter the workflow. Papers consider AI-assisted programming and memory safety, how large language model (LLM) coding tools are evaluated, and whether language choice should change when AI writes much of the code. Two others review programming languages used in robotics and describe a bug tracking system written in plain Python. Of interest to students and developers.
What's in this issue
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AI-Assisted Programming, Memory Safety, Multi-Paradigm Design and Emerging Development Models
This paper surveys AI tools for code generation, explanation, error detection, test generation and translation between languages, alongside memory-safe programming and multi-paradigm design. It argues for a human-in-the-loop approach in which developers set requirements and check AI-generated code. Correctness, security and verification remain open problems.
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LLM-Assisted Programming: Trends, Evaluation Gaps, and Software Assurance
Benchmarks for AI coding tools often test small, isolated tasks. This study examines how the evaluation of LLM-assisted programming has developed, from function-level to repository-level and agent-based tasks, and which problems remain hard to capture, including incorrect API use, weak test oracles and insecure generated code.
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AI-Native Programming Languages: Reconsidering Programming Language Selection in the Era of Generative AI and Autonomous Coding
Language choice has been judged on speed, syntax, portability and popularity. This paper argues that generative AI and autonomous coding add a new dimension to that choice and asks how programming languages should be reconsidered when developers work with large language models and coding agents.
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Programming Languages for Robotics: A Comprehensive Review of Applications, Features, and System Integration
This comparative review of programming languages for robots covers C/C++, Python, Java, C#/.NET and MATLAB, looking at hardware interaction, development environments, simulation support, software integration and suitability for different robotic applications.
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Bug Tracking and Resolution System: A Rule-Based and Python-Driven Approach
The authors argue that machine-learning bug trackers can be too expensive for entry-level and self-taught programmers and budget-constrained organisations. This paper instead manages bugs with basic Python and a rule-based approach, with no black-box models. The authors describe it as still being tested and say it deals adequately with common bugs.