ICSE 2024
Fri 12 - Sun 21 April 2024 Lisbon, Portugal

Software development, inherently a social activity, involves individuals across diverse geographical and cultural settings. Despite this nature, the existing Global Software Engineering research body encounters limitations, making the achieved results challenging to use by practitioners. This Ph.D. research project seeks to overcome these constraints by crafting a theoretical framework. The framework systematically captures cultural differences, exploring their impact on various aspects of software development and delving into practitioners’ strategies for managing these influences. Additionally, the project aims to significantly contribute to the professional software development landscape by transferring research findings to practitioners through practical tools. This framework serves as an immediate application for professionals, fostering project success through heightened cultural awareness and adaptability, thereby enhancing developer well-being in inclusive and culturally diverse environments.

Tue 16 Apr

Displayed time zone: Lisbon change

14:00 - 15:30
Focus Group: Human Aspects, Requirements, and EducationDoctoral Symposium at Fernando Pessoa
Chair(s): Silvia Abrahão Universitat Politècnica de València
14:00
90m
Poster
Investigating Cultural Dispersion: on the Role of Cultural Differences in Software Development Teams
Doctoral Symposium
Stefano Lambiase University of Salerno
Pre-print
14:00
90m
Poster
Generating User Experience Based on Personas with AI Assistants
Doctoral Symposium
Yutan Huang Monash University
14:00
90m
Poster
Building a Framework to Improve the User Experience of Static Analysis Tools
Doctoral Symposium
Michael Schlichtig Heinz Nixdorf Institute, Paderborn University
File Attached
14:00
90m
Poster
MEITREX - Gamified and Adaptive Intelligent Tutoring in Software Engineering Education
Doctoral Symposium
Niklas Meissner University of Stuttgart
DOI File Attached
14:00
90m
Poster
Exploring Strategies for Continuous User Requirement Discovery in ML-Based Software
Doctoral Symposium
File Attached