Computational intelligence and quantitative software engineering. (2016)

• Record Type: Book
• Further Information: Note: Witold Pedrycz, Giancarlo Succi, Alberto Sillitti, editors.
• Editors: Pedrycz, Witold, 1953-; Succi, Giancarlo, 1964-; Sillitti, Alberto
• Contents: Intro; Preface; Contents; 1 The Role of Computational Intelligence in Quantitative Software Engineering; 1 Introduction -- Software Development and the Art of Cappuccino; 2 Persistent Problems in Software Development; 3 Uncertainty; 4 Irreversibility; 5 Complexity; 6 Handling Uncertainty, Irreversibility, and Complexity 2026 and Cappuccino!; 7 The Pivotal Role of Computational Intelligence in Quantitative Software Engineering; 8 Conclusions; References; 2 Computational Intelligence: An Introduction; Abstract; 1 Introduction 2 Computational Intelligence: An Agenda of Synergy of Algorithms of Learning, Optimization and Knowledge Representation3 Neural Networks and Neurocomputing; 4 Evolutionary and Biologically Inspired Computing: Towards a Holistic View at Global Optimization; 5 Information Granularity and Granular Computing; 6 Formal Platforms of Information Granularity; 6.1 Information Granules of Higher Type and Higher Order; 6.2 Hybrid Models of Information Granules; 7 The Concept of Information Granulation-Degranulation; 8 Clustering as a Means of Design of Information Granules 8.1 Unsupervised Learning with Fuzzy Sets8.2 Fuzzy C-Means as an Algorithmic Vehicle of Data Reduction Through Fuzzy Clusters; 8.3 Knowledge-Based Clustering; 9 Computational Intelligence and Software Engineering; 10 Conclusions; References; 3 Towards Benchmarking Feature Subset Selection Methods for Software Fault Prediction; Abstract; 1 Introduction; 2 Related Work; 3 Feature Subset Selection (FSS) Methods; 3.1 Information Gain (IG) Attribute Ranking; 3.2 Relief (RLF); 3.3 Principal Component Analysis (PCA); 3.4 Correlation-Based Feature Selection (CFS) 3.5 Consistency-Based Subset Evaluation (CNS)3.6 Wrapper Subset Evaluation (WRP); 3.7 Genetic Programming (GP); 4 Experimental Setup; 5 Results and Analysis; 6 Validity Evaluation; 7 Conclusions; References; 4 Evolutionary Computation for Software Product Line Testing: An Overview and Open Challenges; Abstract; 1 Introduction; 2 Background; 2.1 SPL Foundations -- Feature Models and Running Example; 2.2 Basics of Evolutionary Algorithms; 3 Overview of SPL Testing; 4 Combinatorial Interaction Testing for Software Product Lines; 4.1 Basic Terminology; 4.2 SPL Genetic Solver (SPLGS) 4.3 State of the Art CIT for SPL Testing5 Multi-objective SPL Testing; 5.1 Multi-objective Optimization Formalization; 5.2 An Example Scenario; 5.3 Computation of Exact Pareto Fronts; 5.4 Sate of the Art in Evolutionary Multi-objective Optimization for SPL Testing; 6 Evolutionary Testing of SPLs in Practice; 7 Open Challenges and Questions; 8 Conclusions; Acknowledgments; References; 5 Metaheuristic Optimisation and Mutation-Driven Test Data Generation; Abstract; 1 Introduction; 2 Test Data Generation; 3 Mutation Analysis; 4 Metaheuristic Optimisation
• Publisher Details: Cham : Springer
• Publication Date: 2016
• Extent: 1 online resource (ix, 207 pages), illustrations (some color)
• Subjects: 006.3; Engineering; Software engineering; Computational intelligence; Computational intelligence; Software engineering; Engineering; Computational Intelligence; Artificial Intelligence (incl. Robotics); Software Engineering; Computers -- Intelligence (AI) & Semantics; Computers -- Software Development & Engineering -- General; Artificial intelligence; Software Engineering; Artificial intelligence; Electronic books
• Languages: English
• ISBNs: 9783319259642; 3319259644; 3319259628; 9783319259628
• Related ISBNs: 9783319259628
• Notes: Note: Online resource; title from PDF title page (SpringerLink, viewed January 21, 2016).
• Access Rights: 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.