27th International Conference, PROFES 2026, Karlskrona, Sweden, November 30–December 2, 2026, Proceedings
Buch, Englisch, Format (B × H): 155 mm x 235 mm
Reihe: Lecture Notes in Computer Science
ISBN: 978-3-032-45953-4
Verlag: Springer
This book constitutes the refereed proceedings of the 27th International Conference on Product-Focused Software Process Improvement, PROFES 2026, held in Karlskrona, Sweden, during November 30- December 2, 2026.
The 28 full papers, 14 short papers, 13 industry papers, 3 doctoral symposium and 5 QuEMaLeS 2026 Workshop papers included in this book were carefully reviewed and selected from 120 submissions. The main theme of PROFES 2026 was professional software process improvement (SPI), motivated by product, process, and service quality needs.
Zielgruppe
Research
Autoren/Hrsg.
Weitere Infos & Material
.- Full Research Papers.
.- Beyond Establishing the Four-Day Workweek: Understanding Adaptation and Long-Term Survival in an Agile Software Organization.
.- Developing a Roadmap to an AI-first Organization: A Case Study in Embedded Software Development.
.- Tag-Aware High-Priority Issue Classification.
.- A Model-Driven Automation Pipeline for Building Operation.
.- A Teacher-Centered Intelligent Tutoring System for Software Process Education: A Design Science Research Approach.
.- Hierarchical Code Knowledge Graphs in AI-Native Software Development.
.- AAS-RAIL: Improving Information Extraction for Asset Administration Shells through Retrieval-Augmented In-Context Learning.
.- From Data Quality to Data Trustworthiness in AI-Driven Software-Intensive Embedded Systems: A Systematic Review.
.- Who Changed the AI Agent's Rules? Measuring How AI Coding Agents Escalate Authority in CI/CD Pipelines.
.- Rethinking Data Quality for AI-Driven Systems: Evidence from Practitioner Interviews.
.- How to simulate human behavior: A Systematic Literature Review.
.- An Industrial Evaluation of DeepQuali: Assessing User Story Quality with Large Language Models.
.- Understanding AI Assistance in Professional Software Engineering: An Interview Study of Development Practices and Workflows.
.- Using Agentic AI for contextualized and multifaceted code review at Ericsson.
.- Generative AI In Software Engineering May Bring Diverse Changes: Industrial Multi-Case Study Findings.
.- Contradictions in AI-Supported Software Development: An Activity Theory Perspective.
.- On the Impact of Requirement Smells in LLM-Based Code Generation.
.- Evidence-Calibrated Runtime Reconstruction for Agent Skills Across Heterogeneous Coding Agents.
.- POMify: LLM-Assisted Refactoring of Selenium Test Suites toward the Page Object Model.
.- Exploring Large Language Model Operations (LLMOps) and Related Challenges in Production Environments: A Systematic Mapping Study.
.- Delegation Without Abdication: A Qualitative Study of Developers' Motivational Needs in AI-Assisted Software Development.
.- Ask the Peers: Ranking NFR Coverage Gaps for Requirements Review.
.- From Code to Clones: A Hybrid Pipeline Combining Classical, Embedding-Based, and LLM-Based Code Clone Detection.
.- Does Agent Configuration Matter? An Empirical Study of Process-Level Quality Adaptation in Multi-Agent Requirements Engineering.
.- From Perception to Practice: How Agile Coaches Create Value in Organisations.
.- Managing User Feedback in Dynamic Scenarios: An Empirically Grounded Reference Model.
.- Does Structured Context Help? A Flowchart-Based Intermediate Representation for LLM-Driven Code Translation.
.- CodeAssay: A Multi-Metric Benchmark with Audited Ground Truth for LLM Code Generation.
.- Short Research Papers.
.- Practical Challenges of Value Stream Mapping in Software-Defined Vehicle Development.
.- Agentic AI in Industry: Adoption Level and Deployment Barriers.
.- From Perception to Action: Can UI Interventions Foster Sustainable LLM Chatbot Use?.
.- A Taxonomy of Dataset Changes for Supporting Machine Learning Pipeline Evolution.
.- When Coding Outpaces Understanding: Making Cognitive Debt Observable in AI-driven SE.
.- Building an Experimentation Knowledge Repository for Organizations: Enabling Reuse and Synthesis of Online Experiment Knowledge.
.- Machine Learning-Based Detection of MCP Attacks.
.- Is Your Testing Scenario Set Good Enough? A Quality Evaluation Framework for Automated Driving Systems.
.- Towards Automatic Generation of Component Diagrams.
.- Generative AI in Software Testing: Practitioners' Perspectives on the Benefits, Challenges, Opportunities, and Risks.
.- A Framework for Risk Management in Innovative Artificial Intelligence Projects: The COSMIC-Risk Design.
.- RepairCAT: Autonomous LLM-Based Program Repair with Reasoning and Targeted Mutation.
.- From Detection to Refactoring: A Controlled Study of LLMs for Java Code Smells.
.- Beyond Trace Transcription: A Test-Aware LLM Workflow for Reconstructing UML Sequence Diagrams.
.- Industry Papers.
.- Migrating Legacy COBOL CI/CD Pipelines: An Industrial Case Study.
.- From First Project to Professional Competence: How Building Automation Engineers Develop Competence and What Transfers Between Systems.
.- Can TDD improve the quality of LLM-migrated code? A pilot study in an industrial context.
.- Orchestrating AI-Assisted Code Remediation: Socio-Technical Bottlenecks in a Large Industrial Repository.
.- From Predicting Churn to Managing It: A Practitioner-Grounded Process Framework for B2B SaaS.
.- From Generated Patches to Verified Fixes: A Validation-Aware Pipeline for LLM-Based Technical Debt Remediation in Industry.
.- Helpful but Fallible: Developer Experiences of AI Tools Under a Coordinated Industrial Rollout.
.- How GenAI Reshapes Software Testing: Changes in Process and Roles.
.- Unified Mobile Ecosystems: A Monorepo Approach for Managing Multi-App React Native Projects at Scale.
.- Supporting Industrial Test-Failure Analysis with LLM-Based Systems: An Experience Report.
.- Adoption Patterns and Governance of AI Coding Assistants in Practice.
.- CAFE: A Context-Aware Framework for Selecting Third-Party Software Tools – An Industrial Case Study of Web API Fuzzing.
.- From Pixels to Structured Interaction: An Industrial Study of MCP-Driven LLM Agents for UI Test Automation.
.- Doctoral Symposium.
.- Verification and Validation of LLM-Enabled Systems.
.- From Adoption to Value: Understanding the Impact of GenAI on Productivity and Value Delivery in Software Engineering.
.- ECOMod: Design-Time Prediction of AI-Model Inference Energy for Sustainable Software Engineering.
.- QuEMaLeS 2026 Workshop.
.- Semantic Mission Invariance Testing for LLM-Based Drone Agents.
.- From Scores to Stable Evidence: Evaluating Structured Outputs in a Stochastic ML Software Pipeline.
.- A Survey of Quality Characteristics for Code-Generating Large Language Models.
.- Beyond Accuracy, MACs, and Latency: Measured Energy as a Quality Measure for Object Detector Selection.
.- Measuring the Quality of LLM Code-Generation Systems.
