=====AI-assisted Software Engineering and Intelligent Development Environments=====

This research area focuses on the application of Artificial Intelligence, Large Language Models (LLMs), and intelligent agents in modern software engineering and next-generation development environments. The research explores how AI can support software analysts, architects, and developers during requirements engineering, behavioral modeling, system design, code generation, documentation, testing, and software maintenance.

Particular attention is given to intelligent development environments (AI-IDE) integrating Generative AI with workflow-oriented software engineering, behavioral analysis, and automated reasoning. The research investigates methods for creating semantically consistent, explainable, and high-quality software artifacts while reducing inconsistencies, technical debt, and design errors introduced during AI-assisted development.

The area also includes collaborative and autonomous AI agents supporting software teams, workflow-aware software analysis, and mechanisms improving reliability, transparency, and quality of AI-generated artifacts. Special attention may also be devoted to AI-assisted development and verification of blockchain-based systems and smart contracts.

Another important direction concerns AI-driven bots and conversational agents supporting correctness-by-construction software development. This includes intelligent assistants generating formally consistent behavioral models, workflows, specifications, and implementation artifacts while supporting automated consistency checking and software quality assurance throughout the development lifecycle.

The research combines AI-assisted Software Engineering (AI4SE), intelligent development environments, software modeling, workflow intelligence, and trustworthy AI-oriented system analysis. Expected outcomes include AI-enhanced development tools, intelligent software engineering frameworks, and advanced environments supporting future AI-driven software engineering processes.

=== See also ===

  * **Radoslaw Klimek**, [[https://www.sciencedirect.com/science/article/pii/S2352220818300889|Pattern-based and composition-driven automatic generation of logical specifications for workflow-oriented software models]]. Journal of Logical and Algebraic Methods in Programming, 2019, vol. 104, pp. 201–226. DOI: 10.1016/j.jlamp.2019.02.005.
  * **Radosław Klimek**, [[https://dl.acm.org/doi/10.1145/3696630.3730562|RE-oriented Model Development with LLM Support and Deduction-based Verification]]. 33rd ACM International Conference on the Foundations of Software Engineering (FSE Companion '25), Trondheim, Norway, 2025, pp. 1–8. DOI: 10.1145/3696630.3730562.
  * **Radoslaw Klimek**, [[https://ieeexplore.ieee.org/document/10765085|Logical square-driven and state-oriented generation of behavioural models]]. 39th IEEE/ACM International Conference on Automated Software Engineering Workshops (ASEW-ASYDE 2024), Sacramento, California, USA, 2024, pp. 72–81. DOI: 10.1145/3691621.3694936.
  * Hou, X. et al., [[https://dl.acm.org/doi/10.1145/3695988|Large Language Models for Software Engineering: A Systematic Literature Review]], ACM Transactions on Software Engineering and Methodology, Vol. 33, No. 8, 2024, pages 1-79. DOI: 10.1145/3695988.