Call for Papers - ASE Special Issue on “Search-Based Software Engineering in the Era of LLMs and Agentic Systems”

A special issue of the Automated Software Engineering Journal.

Description of the Special Issue

This special issue in the Automated Software Engineering journal is intended to provide practitioners and researchers with a venue to present insights, innovations, and solutions in the construction and/or application of Search-Based Software Engineering (SBSE).

SBSE has established itself as a powerful paradigm for addressing complex software engineering problems by formulating them as optimization and search tasks. Over the past two decades, SBSE has successfully tackled challenges across the software lifecycle, including testing, refactoring, configuration, maintenance, program repair, and project management. By leveraging techniques such as evolutionary algorithms, swarm intelligence, multi-objective optimization, and hybrid search strategies, SBSE has enabled scalable solutions to problems that are otherwise difficult to solve analytically.

In parallel, recent advances in Large Language Models (LLMs) and agentic AI systems are transforming the landscape of software engineering. LLMs are now capable of generating code, summarizing repositories, reasoning about program behavior, and assisting developers in tasks such as debugging, testing, and documentation. Moreover, AI agents capable of autonomous reasoning, planning, and tool use are beginning to perform complex software engineering tasks with limited human intervention. These developments open new opportunities and research challenges for SBSE. Search techniques can be used to guide and optimize LLM-driven workflows, explore large solution spaces generated by AI systems, and improve the reliability, efficiency, and controllability of autonomous software engineering agents. Conversely, LLMs can augment SBSE by providing semantic knowledge, search guidance, and program understanding capabilities that were previously unavailable. LLMs also enable automated algorithm design for SBSE, including the generation of new search architectures, solution representations, objective functions, and variation operators tailored to user-defined optimization goals. They can further assist in characterizing the optimization problem and available features, suggesting suitable search strategies, and generating descriptions of candidate algorithms or novel hybrid metaheuristics for further exploration and evaluation.

This special issue aims to bring together the SBSE and AI-for-SE communities to explore how search-based techniques can evolve and thrive in the era of LLMs and agentic AI. We seek high-quality submissions that present novel algorithms, hybrid techniques, empirical studies, industrial experiences, and visionary perspectives advancing the foundations and applications of SBSE in modern AI-driven development environments.

Submission Topics

We invite submissions presenting novel research contributions, empirical studies, and industrial experiences on topics including, but not limited to:

  • Advances in SBSE Methods: Novel optimization algorithms, multi-objective search techniques, scalable search methods, and human-in-the-loop SBSE approaches tailored for modern software engineering challenges.
  • Search-Based Optimization for AI-Assisted Development: Applying SBSE to optimize workflows involving AI-generated code, including testing, debugging, repair, refactoring, and quality assurance of LLM-produced software artifacts.
  • SBSE and Large Language Models: Search-guided prompting, prompt optimization, hybrid SBSE–LLM systems, and the use of LLMs to guide or enhance search processes in software engineering tasks.
  • Agentic AI and Autonomous Software Engineering: Search and optimization techniques for planning, coordination, and control of AI agents performing complex software engineering tasks, including multi-agent systems and autonomous development pipelines.
  • Empirical Studies, Benchmarks, and Industrial Applications: Empirical evaluations, reproducibility studies, benchmarks, and datasets, and real-world applications of SBSE in industrial environments and modern DevOps ecosystems.

Submission Guidelines and Extended Versions

This special issue is an open call to the entire research community.

In addition to the open call for papers, all authors with an accepted paper to SSBSE 2026 are encouraged to submit extended versions of their work. To ensure substantial contributions beyond the conference version, submissions must meet the following criteria:

  • Revised Title: A distinct title differentiating the journal submission from the conference paper.
  • New Content: At least 30% novel material (e.g., expanded experiments, additional theoretical insights, or new applications).
  • Clear Discussion: A detailed explanation of how the journal version builds upon the original conference paper.

Schedule

Opening date for submissions: July 15, 2026

Submission Deadline: January 30, 2027

Submission Instructions

Submissions should conform to the journal’s formatting requirements and will undergo rigorous peer review. Authors are encouraged to include supplementary materials (e.g., datasets or experimental results) to enhance reproducibility. Further details on submission deadlines and procedures will be announced soon. Submission link: via Springer

Editors of the Special Issue

  • Wesley K. G. Assunção, NC State University, USA (corresponding guest editor)
  • Mijung Kim, UNIST, South Korea
  • Ali Ouni, ETS Montreal, University of Quebec, Canada