LASD@ISD'25

Motivation

While agile and lean software development has already become mainstream in industry and a strong community has crystallized around the new way of thinking, making the transition to the new mindset is still challenging for many project managers. Besides, as the vast majority of software development projects are unique, agile methods often need to be tailored to accommodate specific situations. However, method tailoring is not trivial and poses serious challenges for practitioners. Indeed, one of the most distinctive features of Scrum is that its practices are not independent, but instead are very tightly coupled and synergistic.

Furthermore, Scrum, XP, and Kanban were originally designed for small, single teams and do not provide guidance on dealing with scaling issues, while the last decade has seen the spread of agile into large-scale and distributed projects. To help companies in large-scale transformations, several agile scaling frameworks have been proposed. These off-the-shelf solutions incorporate predefined workflow patterns to deal with issues related to the large number of teams, inter-team coordination, and lack of up-front architecture. Nevertheless, numerous challenges while adopting off-the-shelf frameworks have been reported, including a mismatch between framework and organization, changes in management structure, changes in company policies, and the impossibility of fully implementing the whole framework at once.

On top of that, the COVID-19 pandemic has forced co-located teams, who relied on face-to-face communication for work coordination, to transition into a remote work environment. Since agile methods lack guidelines for remote work, it falls upon the agile community to develop systematic solutions for remote agile teams.

Currently, we are witnessing a pervasive hype surrounding generative AI coding tools that leverage Large Language Models (LLMs). These tools enable developers to accelerate coding, testing, debugging, refactoring, and documentation processes. Additionally, fine-tuned LLMs hold the potential for enhancing non-programming tasks like user story refinement, estimation, and prioritization. These remarkable advancements not only evoke excitement but also open up new research directions to further explore and optimize the integration of generative AI tools within the realm of Agile Software Development.

Topics of Interest

Submissions

We invite research papers in three categories: Full Papers (12 pages), Short Papers (8 pages), and Posters (4 pages). Authors have the option to add a single extra page at a supplementary cost (regardless of the submission category). Papers must be in English and present original, not already published research. Papers should be submitted in the PDF format using the ISD template.

Each submission will be reviewed by at least three program committee members. To facilitate the double-blind reviewing, authors are kindly requested to provide the paper WITHOUT any reference to any of the authors, including the authors' personal details, the acknowledgments section of the paper and any other reference that may disclose the authors' identity.

Important Dates

Program

TBA...

Track Chairs

• Neumann, Michael
  Germany, Hochschule Hannover, michael.neumann@hs-hannover.de

• Przybyłek, Adam
  Poland, Gdańsk University of Technology, adam.przybylek@gmail.com

• Wang, Xiaofeng
  Italy, University of Bolzano, Xiaofeng.Wang@unibz.it

Program Commitee

TBA...