Product-Focused Software Process Improvement

This book constitutes the refereed proceedings of the 24th International Conference on Product-Focused Software Process Improvement, PROFES 2023, which took place in Dornbirn, Austria, in December 2023.
The 21 full technical papers, 8 short papers, and 1 poster paper presented in this volume were carefully reviewed and selected from 82 submissions. The book also contains one tutorial paper, 12 and workshop papers and 3 doctoral symposium papers.
The contributions were organized in topical sections as follows:
Part I: Software development and project management; machine learning and data science; software analysis and tools; software testing and quality assurance; security, vulnerabilities, and human factors;
Part II: Posters; Tutorials; 2nd Workshop on Computational Intelligence and Software Engineering (CISE 2023); 2nd Workshop on Engineering Processes and Practices for Quantum Software (PPQS' 23); doctoral symposium.

Inhalt
** Software Development and Project Management.-Virtual Reality Collaboration Platform for Agile Software Development.-Effects of Ways of Working on Changes to Understanding of Benefits Comparing Projects and Continuous Product Development.-To Memorize or to Document: A Survey of Developers' Views on Knowledge Availability.-Facilitating Security Champions in software projects - an experience report from Visma.-Benefits and Challenges of an Internal Corporate Accelerator in a Software Company: An Action-Research Study.-A Process for Scenario Prioritization and Selection in Simulation-Based Safety Testing of Automated Driving Systems.-The Journey to Serverless Migration: An Empirical Analysis of Intentions, Strategies, and Challenges.-On the Role of Font Formats in Building Efficient Web Applications.-Web Image Formats: Assessment of Their Real-World-Usageand Performance across Popular Web Browsers.- Machine Learning and Data Science.- Operationalizing Assurance Cases for Data Scientists: A Showcase of Concepts and Tooling in the Context of Test Data Quality for Machine Learning.-Status Quo and Problems of Requirements Engineering for Machine Learning: Results from an International Survey.-A Stochastic Approach Based on Rational Decision-Making for Analyzing Software Engineering Project Status.-CAIS-DMA: A Decision-Making Assistant for Collaborative AI Systems.-Comparing machine learning algorithms for medical time-series data.- What Data Scientists (Care to) Recall.- Software Analysis and Tools.-Using AI-Based Code Completion for Domain Specific Languages.-Assessing IDEA Diagrams for Supporting Analysis of Capabilities and Issues in Technical Debt Management.- Automatic Fixation of Decompilation Quirks Using Pre-Trained Language Model.-Log Drift Impact on Online Anomaly Detection Workflows.-Leveraging Historical Data to Support User Story Estimation.- Design Patterns Understanding and Use in the Automotive Industry: An Interview Study.- Software Testing and Quality Assurance.-An Experience in the Evaluation of Fault Prediction.-Is It the Best Solution? Testing An Optimisation Algorithm with Metamorphic Testing.-Impacts of Program Structures on Code Coverage of Generated Test Suites.-Anomaly Detection Through Container Testing: A Survey of Company Practices.-The Effects of Soft Assertion on Spectrum-based Fault Localization.-Characterizing Requirements Smells.-Do Exceptional Behavior Tests Matter on Spectrum-based Fault Localization.-On Deprecated API Usages: an Exploratory Study of Top-starred Projects on GitHub.- Security, Vulnerabilities, and Human Factors.-Evaluating Microservice Organizational Coupling based on Cross-service Contribution.-On Fixing Bugs: Do Personality Traits Matter.- A Rapid Review on Software Vulnerabilities and Embedded, Cyber-Physical, and IoT Systems.- Social Sustainability Approaches for Software Development: A Systematic Literature Review.-The Testing Hopscotch Model Six Complementary Profiles Replacing the Perfect All-Round Tester.-Continuous Experimentation and Human Factors An Exploratory Study.**