Supporting software engineering tasks with agentic AI: Demonstration on document retrieval and test scenario generation
Gratex International（格拉特克斯国际）；Department of Applied Informatics Faculty of Mathematics, Physics and Informatics Comenius University（应用信息学院数学、物理和信息学院康门ius大学）
Marian Kica, Lukas Radosky, David Slivka, Karin Kubinova, Daniel Dovhun, Tomas Uhercik, Erik Bircak, Ivan Polasek
备注：
This is a preprint of a paper that was accepted at the International Conference on Artificial Intelligence, Computer, Data Sciences and Applications (ACDSA 2026)
The introduction of large language models ignited great retooling and rethinking of the software development models. The ensuing response of software engineering research yielded a massive body of tools and approaches. In this paper, we join the hassle by introducing agentic AI solutions for two tasks. First, we developed a solution for automatic test scenario generation from a detailed requirements description. This approach relies on specialized worker agents forming a star topology with the supervisor agent in the middle. We demonstrate its capabilities on a real-world example. Second, we developed an agentic AI solution for the document retrieval task in the context of software engineering documents. Our solution enables performing various use cases on a body of documents related to the development of a single software, including search, question answering, tracking changes, and large document summarization. In this case, each use case is handled by a dedicated LLM-based agent, which performs all subtasks related to the corresponding use case. We conclude by hinting at the future perspectives of our line of research.
Agentic Security: A Systematization of Tools, Failure Modes, and Design Laws for LLM-Driven Penetration Testing
Ahsanullah University of Science and Technology（阿赫桑乌拉科技大学）；BRAC University（BRAC大学）；North South University（北南大学）；Missouri State University（密苏里州立大学）；Multimedia University（多媒体大学）；American International University-Bangladesh（孟加拉国美国国际大学）
Agentic Generation and Evolution of Knowledge Models
Beihang University（北京航空航天大学）；Universidad Nacional de Río Cuarto（里奥夸尔托国立大学）；Guangdong Technion-Israel Institute of Technology（广东以色列理工学院）；CONICET（阿根廷国家科学研究委员会）；University of Buenos Aires（布宜诺斯艾利斯大学）；Imperial College London（帝国理工学院）
