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Software quality : the complexity and challenges of software engineering and software quality in the cloud : 11th International Conference, SWQD 2019, Vienna, Austria, January 15-18, 2019, Proceedings /: the complexity and challenges of software engineering and software quality in the cloud : 11th International Conference, SWQD 2019, Vienna, Austria, January 15-18, 2019, Proceedings. (2019)
Record Type:
Book
Title:
Software quality : the complexity and challenges of software engineering and software quality in the cloud : 11th International Conference, SWQD 2019, Vienna, Austria, January 15-18, 2019, Proceedings /: the complexity and challenges of software engineering and software quality in the cloud : 11th International Conference, SWQD 2019, Vienna, Austria, January 15-18, 2019, Proceedings. (2019)
Main Title:
Software quality : the complexity and challenges of software engineering and software quality in the cloud : 11th International Conference, SWQD 2019, Vienna, Austria, January 15-18, 2019, Proceedings
Other Titles:
SWQD 2019
Further Information:
Note: Dietmar Winkler, Stefan Biffl, Johannes Bergsmann (eds.).
Multi-Disciplinary Systems and Software Engineering.- Multi-Disciplinary Engineering of Production Systems – Challenges for Quality of Control Software.- Towards a Flexible and Secure Round-Trip-Engineering Process for Production Systems Engineering with Agile Practices.- Software Quality and Process Improvement.- Relating Verification and Validation Methods to Software Product Quality Characteristics: Results of an Expert Survey.- Listen to Your Users – Quality Improvement of Mobile Apps through Lightweight Feedback Analyses.- Agile Software Process Improvement by Learning from Financial and Fintech Companies: LHV Bank Case Study.- Software Testing.- Why Software Testing Fails: Common Pitfalls Observed in a Critical Smart Metering Project.- Knowledge Engineering and Machine Learning.- Mixed Reality Applications in Industry: Challenges and Research Areas.- Improving Defect Localization by Classifying the Affected Asset using Machine Learning.- Source Code Analysis.- Benefits and Drawbacks of Representing and Analyzing Source Code and Software Engineering Artifacts with Graph Databases.- Software Maintenance.- Evaluating Maintainability Prejudices with a Large-Scale Study of Open-Source Projects.
Note: Online resource; title from PDF title page (SpringerLink, viewed January 16, 2019).
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Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
Access Usage:
Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.