Managed Software Evolution.

• Author: Reussner, Ralf.
• TeilnehmendeR: Goedicke, Michael.; Hasselbring, Wilhelm.; Vogel-Heuser, Birgit.; Keim, Jan.; Märtin, Lukas.
• Place / Publishing House: Cham : : Springer International Publishing AG,, 2019.; ©2019.
• Year of Publication: 2019
• Edition: 1st ed.
• Language: English
• Physical Description: 1 online resource (439 pages)

Table of Contents

Intro -- Foreword -- Contents -- Contributors -- International Board of Reviewers -- Acronyms -- Part I Introduction -- 1 Introducing Managed Software Evolution -- 2 The Nature of Software Evolution -- 2.1 Introduction -- 2.2 Software Systems -- 2.2.1 Application Domains -- 2.2.2 Scopes and Environments of Software Systems -- 2.2.3 Software Artefacts -- 2.2.4 Software Variants -- 2.3 Software Quality -- 2.3.1 Consistency -- 2.3.2 Correctness -- 2.3.3 Dependability -- 2.3.4 Performance -- 2.3.5 Usability -- 2.3.6 Maintainability -- 2.4 Software Evolution -- 2.4.1 Kinds of Software Change -- 2.4.2 Evolution Processes -- 2.4.3 Configuration Management -- 3 Addressed Challenges -- 3.1 Tacit Knowledge -- 3.2 Design Decisions -- 3.3 Software Product Line Round-Trip Engineering -- 3.4 Maintaining Performance -- 3.5 Maintaining Security -- 3.6 Learning from Evolution for Evolution -- 3.7 Maintaining Correctness -- 4 Introduction to Case Studies -- 4.1 Evolution of Long-Living Systems to an Industry 4.0 Case Study -- 4.2 Introduction of the CoCoME Case Study -- 4.2.1 Platform Migration -- 4.2.2 Adding a Pick-Up Shop -- 4.2.3 Database Migration -- 4.2.4 Adding a Mobile App Client -- 4.2.5 Microservice Architecture -- 4.2.6 Container Virtualization -- 4.2.7 Adding Payment Methods -- 4.3 Introduction of the PPU and xPPU Case Studies -- 4.3.1 Evolution Scenarios of the PPU -- 4.3.2 Incremental Evolution Scenarios -- 4.3.3 Evolution Scenarios of the xPPU -- 4.4 Industry 4.0 Case Study -- 4.4.1 Industry 4.0 Interface of the xPPU -- 4.4.2 Integration of CoCoME and xPPUto Form an Industry 4.0 Case Study -- Part II Knowledge Carrying Software -- 5 Tacit Knowledge in Software Evolution -- 5.1 Toward Identification and Extraction of Tacit Knowledge -- 5.2 Foundations -- 5.3 Tacit Knowledge During Design Time -- 5.3.1 Security in Requirement Documents.

5.3.2 Modelling of Security Knowledge -- Security Ontology -- Representation of Knowledge -- 5.3.3 Identification and Extraction of Tacit Security Knowledge -- Classification of Words -- Measurement of Similarity Between Security Abstraction Models -- (Semi)-Automatic Acquisition of Tacit Knowledge -- 5.3.4 Tacit Security Knowledge Examples -- 5.4 Tacit Knowledge During Run Time -- 5.4.1 Usage Knowledge in Software Evolution -- 5.4.2 Modelling of Knowledge -- 5.4.3 Identification and Extraction of Tacit Usage Knowledge -- Runtime Personas -- Extraction of Tacit Usage Knowledge -- 5.4.4 Tacit Usage Knowledge Examples -- 5.5 Related Work -- 5.6 Conclusion -- 5.6.1 Summary -- 5.6.2 Outlook -- 5.6.3 Further Reading -- 6 Continuous Design Decision Support -- 6.1 Introduction -- 6.1.1 Challenges for a Continuous Design Decision Support -- 6.1.2 Solution Approaches for Design Decision Challenges -- 6.1.3 Structure of This Chapter -- 6.2 Foundations -- 6.3 Using a Design Pattern Catalogue to Make Design Decisions -- 6.3.1 Motivation for Using a Pattern Catalogue -- 6.3.2 Decision-Making Process Using a Pattern Catalogue -- 6.3.3 Application to the Case Study -- 6.4 Integrating Design Decision Models with Program Code -- 6.4.1 Integrating Architecture Models with Code -- 6.4.2 Design Decisions, Rationale, and Patterns in the IAL -- 6.4.3 Application to the Case Study -- 6.5 Continuous Management of Decision Knowledge -- 6.5.1 Integrating Design Decisions into CSE -- 6.5.2 Decision Knowledge Triggers -- Making Tacit Decisions Explicit -- Packaging Distributed Decision Knowledge -- Considering Consistency Between Decisions -- 6.5.3 Application to the Case Study -- Scenario for the Explicit Documentation of Decision Knowledge -- Scenario for Making Tacit Decisions Explicit -- Scenario for Packaging Distributed Decision Knowledge.

Scenario for Considering Consistency Between Decisions -- 6.6 Related Work -- 6.6.1 Documentation Consistent with External Decision Knowledge -- 6.6.2 Documentation of Decision Knowledge Consistent with Architecture and Code -- 6.6.3 Non-intrusive Documentation of Decision Knowledge -- 6.7 Conclusion -- 6.8 Further Reading -- 7 Model-Based Round-Trip Engineering and Testing of Evolving Software Product Lines -- 7.1 Foundations -- 7.1.1 Model-Based Software Development and Testing -- 7.1.2 Model-Based Product-Line Engineering and Testing -- 7.1.3 Product-Line Round-Trip Engineering and Artefact Co-evolution -- 7.2 Evolution -- 7.2.1 Evolution of Software Variants -- 7.2.2 Evolution of Software Product Lines -- 7.2.3 Evolution of Model-Based Testing Artefacts -- 7.3 Co-evolution -- 7.3.1 Co-evolution of Software Product Lines and Product Variants -- 7.3.2 Co-evolution of Software Product Lines and Model-Based Testing Artefacts -- 7.3.3 Co-evolution of Product Variants and Test Artefacts -- 7.4 Conclusion -- 7.5 Further Reading -- 8 Performance Analysis Strategies for Software Variants and Versions -- 8.1 Analysis Strategies for Software Variants -- 8.1.1 Sample-Based Analysis of Software Variants -- 8.1.2 Family-Based Test-Suite Generation for Software Variants -- 8.1.3 Family-Based Analysis of Software Variants -- 8.2 Analysis Strategies for Software Versions -- 8.2.1 Declarative Analysis Strategies for Evolving Software -- 8.2.2 Align Development-Level Evolution and Operation-Level Adaptation -- 8.2.3 Co-evolution of Architecture and Analysis Models -- Sequence Diagram to Layered Queueing Network -- State Charts to Continuous Time Markov Chains -- Analysis of LQN and CTMC Models with Model Solvers -- 8.3 Conclusion and Road Map -- 9 Maintaining Security in Software Evolution -- 9.1 Foundations.

9.2 Design Time: Leveraging Knowledge from Natural Language for Design-Time System Adaptation -- 9.2.1 Overview -- 9.2.2 Capturing Security Requirements Using Natural-Language Processing -- 9.2.3 Representing Security Knowledge Using Ontologies -- 9.2.4 Rule-Based Model Co-evolution -- 9.2.5 Related Work -- 9.2.6 Leveraging Security Knowledge to Infer Adequate Reaction to Context Changes -- 9.2.7 Summary -- 9.3 Integrating Model-Based Security Constraints with Program Code -- 9.3.1 Codeling: Integrating Architecture Model Information with Program Code -- 9.3.2 Application: Security Evolution Scenario -- 9.3.3 Security Aspects in the Intermediate Architecture Language -- 9.3.4 Integrating Security-Architectures with Code Using the Model Integration Concept -- 9.3.5 Related Work -- 9.3.6 Summary -- 9.4 Contextual Security Patterns -- 9.4.1 Security Challenges in Software Evolution -- 9.4.2 Contextual Security -- 9.4.3 From Design Patterns to Security Patterns -- 9.4.4 Security Patterns as a Means for Contextual Software Security -- 9.4.5 Related Work -- 9.4.6 Summary -- 9.5 Self-adaptive Security Maintenance at Run Time by Identifying Suspicious Behaviour -- 9.5.1 Overview -- Application: Running Example -- 9.5.2 Capturing Context for Security Adaption -- 9.5.3 Leveraging Run-Time Information to Support Design-Time Security Adaption -- 9.5.4 Heuristics-Based Run-Time Assessment to Detect Security Requirement Violations -- 9.5.5 Adaption During Run Time -- 9.5.6 Related Work -- 9.5.7 Summary -- 9.6 Anomaly Detection for Evolving Software Controlled Production Systems at Run Time -- 9.6.1 Overview -- 9.6.2 Detection Model: Machine State Petri Net -- 9.6.3 Anomaly Detection Mechanism -- 9.6.4 Example: Using the PPU Case Study -- 9.6.5 Related Work: Finding Behaviour Anomalies -- 9.6.6 Summary -- 9.7 Conclusion -- 9.8 Further Reading.

10 Learning from Evolution for Evolution -- 10.1 Detailed Analysis of Past Evolutions of Models -- 10.1.1 Analysing Linear Evolution of Monolithic Models -- Motivation and Goals -- Overview of the Approach -- Example Applications -- 10.1.2 Analysing Co-evolution of Coupled Models -- A Generic Framework for Analysing Model Co-evolution -- Case Study on Architecture and Fault Tree Co-evolution -- 10.1.3 Related Work -- 10.1.4 Conclusion -- 10.1.5 Further Reading -- 10.2 Formal Analysis of Planned Changes -- 10.2.1 Using Model-Based Verification of Interdisciplinary Models -- 10.2.2 Using Regression Verification for Small Evolution Steps in PLC-Code -- 10.2.3 Conclusion and Outlook -- 10.3 Analyse Non-functional Aspects of the System -- 10.3.1 Learning and Analysing the Machine States and Material Flow of Evolving ManufacturingSystems -- Three-Phase Evolution Support Process -- Application on xPPU Case Study -- 10.3.2 Learning and Analysing DTMCs for Reliability Evaluation -- Related Work -- Further Reading -- 10.3.3 Conclusion and Outlook -- 10.4 Recommend and Assess Future Changes Basedon Past Changes -- 10.4.1 Supporting Model Editing with Automatic Recommendations -- Foundation -- Analysis of Change Histories -- Inferring Blueprints -- Evaluation -- Related Work -- Conclusion -- 10.4.2 Recommending Evolution Steps Within a Knowledge Carrying Network -- Express Evolution Steps of a System -- Application on xPPU Case Study -- Related Work -- Further Reading -- 10.4.3 Learning Maintainability Estimation for Enabling an ``Economical Effort Recommender'' -- Challenges for Maintainability Estimation: Information Systems vs. Automated Production Systems -- Karlsruhe Architectural Maintainability Prediction for Automated Production Systems: An Architecture-Based Change Impact Analysis Method for aPS -- 10.4.4 Conclusion and Outlook -- 10.5 Conclusion.

11 Formal Verification of Evolutionary Changes.