Software quality : future perspectives on software engineering quality : 13th International Conference, SWQD 2021, Vienna, Austria, January 19-21, 2021 : proceedings

This book constitutes the refereed proceedings of the 13th Software Quality Days Conference, SWQD 2021, which was planned to be held in Vienna, Austria, during January 19-21, 2021. Due to the COVID-19 pandemic, the conference was cancelled and will be merged with SWQD 2022. The Software Quality Days (SWQD) conference started in 2009 and has grown to the biggest conference on software quality in Europe with a strong community. The program of the SWQD conference is designed to encompass a stimulating mixture of practical presentations and new research topics in scientific presentations. The guiding conference topic of the SWQD 2021 is "Future Perspectives on Software Engineering Quality". The 3 full papers and 5 short papers presented in this volume were carefully reviewed and selected from 13 submissions. The volume also contains 2 invited talks and one introductory paper for an interactive session. The contributions were organized in topical sections named: automation in software engineering; quality assurance for AI-based systems; machine learning applications; industry-academia collaboration; and experimentation in software engineering.-- Provided by publisher Preface Message from the Scientific Program Chairs Organization Contents Automation in Software Engineering Assisted Requirements Engineering - What Will Remain in the Hands of the Future Requirements Engineer? (Invited Keynote) 1 Introduction: The World is Changing, RE is Changing, So What Will Remain? 2 Which Steps Do Automations Take? Some Analogies 2.1 Driver Assistance 2.2 Programming 3 Text Analytics Revisited: What is, Will, and Will Never Be Possible? 3.1 What Will Not Change Despite of Text Analytics? 3.2 What Could Change with Text Analytics? 4 A Look into the Crystal Ball: The Role of a Requirements Engineer in Different Levels of Automation 4.1 Phase 1: Decoupled Requirements Engineering 4.2 Phase 2: Assistance Functions in Requirements Engineering 4.3 Phase 3: Partly Automated Requirements Engineering 4.4 Phase 4: Fully Automated Requirements Engineering 5 Summary and Outlook References Testing Autogenerated OPC UA NodeSet Models for Product Variants in Industry 1 Introduction 2 Industrial Context and Related Work 3 Approach and Implementation 3.1 Test Project Generator (TPG) 3.2 Test Metadata Exporter (TME) 3.3 Test Execution (TE) 4 Results and Discussion 4.1 Test Execution Data 4.2 General Findings 5 Conclusion and Outlook References Quality Assurance for AI-Based Systems Quality Assurance for AI-Based Systems: Overview and Challenges (Introduction to Interactive Session) 1 Introduction 2 Background and Terminology 3 Challenges 4 Summary and Conclusions References Software Quality for AI: Where We Are Now? 1 Introduction 2 Related Work 3 AI Software Quality: Key Issues and Comments 4 Research Roadmap 5 Conclusion References Hidden Feedback Loops in Machine Learning Systems: A Simulation Model and Preliminary Results 1 Introduction 2 Background and Related Work 3 Problem Statement 3.1 Motivating Example 3.2 Formal Statement 4 Methods 4.1 Simulation Experiment 4.2 Experiment Setup 4.3 Results and Observations 5 Analysis and Discussion 5.1 Existence Conditions for a Positive Feedback Loop 5.2 Checklist for Detecting Feedback Loops 6 Future Research 7 Conclusion References The AIQ Meta-Testbed: Pragmatically Bridging Academic AI Testing and Industrial Q Needs 1 Introduction 2 Background and Related Work 3 AI Quality Assurance – Working Definitions 4 AIQ – An AI Meta-Testbed 5 Summary and Concluding Remarks References Machine Learning Applications Improving Quality of Code Review Datasets – Token-Based Feature Extraction Method 1 Introduction 2 Related Work 3 New Feature Extraction Method 4 Research Design 4.1 Case Selection 4.2 Data Collection 4.3 Data Analysis 5 Results 6 Conclusions References Is Machine Learning Software Just Software: A Maintainability View 1 Introduction 2 Background: ML Explained for Programmers 3 Challenges with an ML Component and Experiences from a Sample Project 4 ML in the Light of Maintainability 5 Discussion 6 Conclusions References Industry-Academia Collaboration Solving Problems or Enabling Problem-Solving? from Purity in Empirical Software Engineering to Effective Co-production (Invited Keynote) 1 Introduction 2 The Problem(s) with ``Software'' 2.1 Inception and Engineering 2.2 Human-Centric Activities 2.3 Delivery 3 Research with and in Industry 4 Discussion References Experimentation in Software Engineering An Empirical Study of User Story Quality and Its Impact on Open Source Project Performance 1 Introduction 2 Related Work 2.1 Quality of User Stories 2.2 Empirical Studies on the Impact of Requirements Quality 2.3 Time Series Analysis in Software Engineering 2.4 Summary 3 Study Design 3.1 Research Questions 3.2 Initial Dataset 3.3 Data Cleaning 3.4 Measurement 3.5 Data Analysis 4 Results 4.1 Study Population 4.2 User Stories Quality Monitoring and Evolution Patterns 4.3 User Story Quality and Project Performance 5 Discussion 6 Limitations 7 Conclusion References An Approach for Platform-Independent Online Controlled Experimentation 1 Introduction 2 Background 2.1 Online Controlled Experimentation 2.2 Characteristics of Online Controlled Experiments 2.3 Experimentation Definition Language 3 Research Method 4 Experiment Definition's Qualities and Roles 4.1 Qualities 4.2 Roles 5 Platform-Independent Experimentation 5.1 Requirements 5.2 Architecture 6 Evaluation 6.1 Scenario 6.2 System Overview 6.3 Feasibility 6.4 Platform-Independence 6.5 Experimental Result 7 Discussion 8 Conclusions References Author Index