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Component-Based Software Quality [[electronic resource] ] : Methods and Techniques / / edited by Alejandra Cechich, Mario Piattini, Antonio Vallecillo
| Component-Based Software Quality [[electronic resource] ] : Methods and Techniques / / edited by Alejandra Cechich, Mario Piattini, Antonio Vallecillo |
| Edizione | [1st ed. 2003.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2003 |
| Descrizione fisica | 1 online resource (X, 410 p.) |
| Disciplina | 005.3 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Computer industry
Software engineering Management information systems Computer science The Computer Industry Software Engineering Management of Computing and Information Systems |
| ISBN | 3-540-45064-5 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Assessing Component-Based Systems -- Assessing Component-Based Systems -- I COTS Selection -- COTS-Based Requirements Engineering -- Domain-Based COTS-Product Selection Method -- STACE: Social Technical Approach to COTS Software Evaluation -- SCARLET: Integrated Process and Tool Support for Selecting Software Components -- II Testing and Certification -- Component-Based Software: An Overview of Testing -- Setting a Framework for Trusted Component Trading -- Component Integration through Built-in Contract Testing -- III Software Component Quality Models -- Quality Characteristics for Software Components: Hierarchy and Quality Guides -- Driving Component-Based Software Development through Quality Modelling -- Towards a Quality Model for the Selection of ERP Systems -- Maturing Architectures and Components in Software Product Lines -- IV Formal Approaches to Quality Assessment -- Assessment of High Integrity Software Components for Completeness, Consistency, Fault-Tolerance, and Reliability -- Reasoning about Software Architectures with Contractually Specified Components -- Reuse of Formal Verification Efforts of Incomplete Models at the Requirements Specification Stage -- V CBSD Management -- Risk Management of COTS Based Systems Development -- A Metrics-Guided Framework for Cost and Quality Management of Component-Based Software. |
| Record Nr. | UNINA-9910143859703321 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2003 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Component-Based Software Quality [[electronic resource] ] : Methods and Techniques / / edited by Alejandra Cechich, Mario Piattini, Antonio Vallecillo
| Component-Based Software Quality [[electronic resource] ] : Methods and Techniques / / edited by Alejandra Cechich, Mario Piattini, Antonio Vallecillo |
| Edizione | [1st ed. 2003.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2003 |
| Descrizione fisica | 1 online resource (X, 410 p.) |
| Disciplina | 005.3 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Computer industry
Software engineering Management information systems Computer science The Computer Industry Software Engineering Management of Computing and Information Systems |
| ISBN | 3-540-45064-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Assessing Component-Based Systems -- Assessing Component-Based Systems -- I COTS Selection -- COTS-Based Requirements Engineering -- Domain-Based COTS-Product Selection Method -- STACE: Social Technical Approach to COTS Software Evaluation -- SCARLET: Integrated Process and Tool Support for Selecting Software Components -- II Testing and Certification -- Component-Based Software: An Overview of Testing -- Setting a Framework for Trusted Component Trading -- Component Integration through Built-in Contract Testing -- III Software Component Quality Models -- Quality Characteristics for Software Components: Hierarchy and Quality Guides -- Driving Component-Based Software Development through Quality Modelling -- Towards a Quality Model for the Selection of ERP Systems -- Maturing Architectures and Components in Software Product Lines -- IV Formal Approaches to Quality Assessment -- Assessment of High Integrity Software Components for Completeness, Consistency, Fault-Tolerance, and Reliability -- Reasoning about Software Architectures with Contractually Specified Components -- Reuse of Formal Verification Efforts of Incomplete Models at the Requirements Specification Stage -- V CBSD Management -- Risk Management of COTS Based Systems Development -- A Metrics-Guided Framework for Cost and Quality Management of Component-Based Software. |
| Record Nr. | UNISA-996466055103316 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2003 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Data Governance : From the Fundamentals to Real Cases / / Ismael Caballero and Mario Piattini, editors
| Data Governance : From the Fundamentals to Real Cases / / Ismael Caballero and Mario Piattini, editors |
| Edizione | [First edition.] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2023] |
| Descrizione fisica | 1 online resource (255 pages) |
| Disciplina | 658.4038 |
| Soggetto topico |
Knowledge management
Management information systems |
| ISBN | 3-031-43773-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Foreword by Yang Lee -- Foreword by Alberto Palomo -- Preface -- Overview -- Organization -- Part I: Data Governance Fundamentals -- Part II: Data Governance Applied -- Target Readership -- Acknowledgments -- Contents -- Contributors -- List of Abbreviations -- Part I: Data Governance Fundamentals -- Chapter 1: Introduction to Data Governance: A Bespoke Program Is Required for Success -- 1.1 Chapter Overview -- 1.2 Why Does Data Need to Be Governed? -- 1.2.1 Long-Lasting Consequences of Poor Data Decisions? -- 1.2.2 Mounting Data Debt -- 1.3 Who Needs to Be Involved in DG? -- 1.4 When Is It Appropriate for Organizations to Invest in DG? -- 1.5 Where Should Organizations Get Started with DG? -- 1.6 How Should Organizations Apportion Their DG Efforts Over Time? -- 1.6.1 Data Debt´s Impact -- 1.6.2 Proactive Versus Reactive DG -- 1.6.3 MacGyver Abilities -- 1.7 What Organizational Needs Does DG Fill? -- 1.7.1 Improving the Ways That Data Is Treated as an Asset? -- 1.7.2 Available but Not Widely Known Research Results -- 1.7.3 Using Data to Better Support the Organizational Mission -- 1.7.4 The Role of DG Frameworks -- 1.7.4.1 Related Term Definitions -- 1.7.4.2 A Small Concentrated Team Is Preferred Over Distributed (Dissipated) Knowledge -- 1.7.5 Using Data Strategically -- 1.7.5.1 Strategy Is About Why -- 1.7.5.2 What Is Data Strategy? -- 1.7.5.3 Working Together: Data and Organizational Strategy? -- 1.7.5.4 Strategic Commitment: Program Versus Project Focus -- 1.7.5.5 Digitizationing -- 1.7.5.6 A Watchful Eye Toward the US Federal Government (FEPA) -- 1.7.6 Breaking Through the Barriers of Data Governance -- 1.8 Chapter Summary -- Chapter 2: Data Strategy and Policies: The Role of Data Governance in Data Ecosystems -- 2.1 Introduction -- 2.2 Data Strategy and Policies -- 2.2.1 Data Strategy Fundamentals.
2.2.2 From Defensive to Offensive Data Strategy -- 2.2.3 Data Policies -- 2.3 New Development Trajectories for Data Governance -- 2.3.1 Data as Strategic Asset for Organizations -- 2.3.2 The Emergence of Data Ecosystems -- 2.4 Widening the Scope of Data Governance Operations -- 2.4.1 Consideration of Challenging External Influencing Factors -- 2.4.2 Bridging the Intra-organizational Perspective on Data Governance with the Inter-organizational Perspective -- 2.5 Utilizing Data Ecosystems as Part of Data Strategy -- 2.5.1 The Role of Ecosystem Data Governance -- 2.5.2 Inter-organizational Data Governance Modes -- 2.5.3 Adequate Positioning for Engaging in Data Ecosystems -- 2.6 Recommendations for Action -- 2.6.1 Recommendations for Actions for Single Organizations -- 2.6.2 Recommendations for Actions for Data Ecosystem Design -- References -- Chapter 3: Human Resources Management and Data Governance Roles: Executive Sponsor, Data Governors, and Data Stewards -- 3.1 Introduction -- 3.2 The Role of Human Resources in Data Governance -- 3.3 Understanding the Structure of the Data Governance Organization -- 3.3.1 Executive Steering Committee -- 3.3.2 Data Governance Board -- 3.3.3 Data Stewardship Council -- 3.3.4 Data Governance Program Office (DGPO) -- 3.3.4.1 Data Governance Program Office (DGPO) Responsibilities -- 3.3.4.2 Data Governance Manager Responsibilities -- 3.3.4.3 Enterprise Data Steward Responsibilities -- 3.4 Key Roles and Responsibilities for Data Stewards -- 3.4.1 Business Data Stewards -- 3.4.2 Technical Data Stewards -- 3.4.3 Operational Data Stewards -- 3.4.4 Project Data Stewards -- 3.5 Summary -- Chapter 4: Data Value and Monetizing Data -- 4.1 Managing Data as an Actual Asset -- 4.1.1 The Emergence of the Chief Data Officer -- 4.1.2 Approaches to Data Asset Management -- 4.1.3 Data´s Emergence as a Real Economic Asset. 4.1.4 The Need for Senior Executive Understanding -- 4.2 Impediments to Maturity in Enterprise Data Management -- 4.2.1 Leadership Issues -- 4.2.2 IM Priorities Over Which You Have Control or Influence -- 4.2.3 Resources Needed to Advance Data Management Capabilities -- 4.2.4 Negative Cultural Attitudes About Data Management -- 4.2.5 Overcoming the Barriers to Data Asset Management -- 4.2.6 Moving Forward -- 4.3 Generally Agreed-Upon Data Principles (GAIP) -- 4.4 Data Supply Chains and Ecosystems -- 4.4.1 Adapting the SCOR Model -- 4.4.2 Metrics for the Data Supply Chain -- 4.5 A New Model for the Data Supply Chain -- 4.6 Data Ecosystems -- 4.6.1 Data Within an Ecosystem -- 4.6.2 Ecosystem Entities -- 4.6.3 Ecosystem Features -- 4.6.4 Ecosystem Processes -- 4.6.5 Ecosystem Influences -- 4.6.6 Ecosystem Management -- 4.7 Applying Sustainability Concepts to Managing Data -- 4.8 Data Management Standards -- 4.8.1 Adapting IT Asset Management (ITAM) to Data Management -- 4.8.2 Adapting ITIL to Data Management -- 4.8.3 Adaptations from RIM and ECM -- 4.8.4 Adaptations from Library Science -- 4.8.5 Adaptations from Physical Asset Management -- 4.8.6 Adaptations from Financial Management -- Chapter 5: Data Governance Methodologies: The CC CDQ Reference Model for Data and Analytics Governance -- 5.1 Introduction -- 5.2 Paradigm Shifts in Data Governance: From Control to Value Creation -- 5.2.1 Data Governance: Definition and Mechanisms -- 5.2.2 Data Governance 1.0: Focus on Control, Data Quality, and Regulatory Compliance -- 5.2.3 Data Governance 2.0: Extending Beyond Control to Enable Value Creation -- 5.2.4 Need for Guidelines Supporting Data and Analytics Governance -- 5.3 The CC CDQ Reference Model for Data and Analytics Governance -- 5.3.1 Data Governance as Key Theme in the Competence Center Corporate Data Quality. 5.3.2 Design Principles for Data and Analytics Governance -- 5.3.2.1 Principle 1: Governance Linking Strategy to Operations -- 5.3.2.2 Principle 2: Federated Data Governance Involving Data and Analytics, Business, and IT Experts -- 5.3.2.3 Overview of the CC CDQ Reference Model for Data and Analytics Governance -- 5.4 Step 1: Set the Scope for Data and Analytics Governance -- 5.4.1 End-to-End Perspective for Defining Scope and Requirements -- 5.4.2 Data and Analytics Products and Their Information Supply Chains -- 5.5 Step 2: Who to Govern? - Processes, Roles, and Responsibilities -- 5.5.1 Decision Areas (Processes) -- 5.5.2 Data and Analytics Roles -- 5.5.2.1 Data Management Roles and Responsibilities -- 5.5.2.2 Analytics Roles and Responsibilities -- 5.5.2.3 Organization-Wide Coordination of Data and Analytics -- 5.5.3 Assigning Roles to Responsibilities -- 5.6 Step 3: How to Govern? - Deriving the Operating Model -- 5.6.1 Mapping Roles, Responsibilities, and Processes to the Organizational Context -- 5.6.1.1 Typical Configurations -- 5.7 Summary -- References -- Chapter 6: Data Governance Tools -- 6.1 Introduction -- 6.2 The Business Need for Data Governance and Its Importance -- 6.2.1 Common Business Outcomes Led by Chief Data Officers -- 6.3 Case Study: Southwest Airlines and the Role of Technology on Business Outcomes -- 6.3.1 Data Challenges in the Transportation Industry -- 6.4 Key Functionalities Needed in the Data Governance Tools -- 6.4.1 Twelve Technology Features Chief Data Officers Can Use to Become Data-Driven -- 6.4.2 Data Governance Technology Challenges -- 6.5 Four Must-Have Technology Focus Areas to Kick-start Data Governance -- 6.5.1 Flexible Operating Model -- 6.5.1.1 Insurance Customer Story -- 6.5.2 Identification of Data Domains -- 6.5.2.1 Financial Services Customer Story. 6.5.3 Identification of Critical Data Elements (CDEs) Within Data Domains -- 6.5.3.1 Federal Government Agency in Washington, D.C., Story -- 6.5.3.2 Technology Company Story -- 6.5.4 Enable Control Measurements -- 6.5.4.1 Technology Company Out of California Story -- 6.6 Conclusion -- Chapter 7: Maturity Models for Data Governance -- 7.1 Introduction -- 7.2 Maturity Models -- 7.2.1 DAMA -- 7.2.2 Aiken´s Model -- 7.2.3 Data Management Maturity (DMM) Model -- 7.2.4 IBM Model -- 7.2.5 Gartner´s Enterprise Information Management Model -- 7.2.6 DCAM -- 7.3 MAMD (Alarcos´ Model for Data Maturity) -- 7.3.1 ISO/IEC 33000 Standards Family -- 7.3.2 MAMD Overview -- 7.3.3 The Capability Dimension -- 7.3.4 Process Dimension -- 7.3.5 Organizational Maturity Model -- 7.4 Practical Applications of MAMD -- 7.4.1 Regional Government: Improving the Performance of Authentication Servers -- 7.4.2 Insurance Company: Building a ``Source of Truth´´ Repository -- 7.4.3 Bicycle Manufacturer: Enabling Better Analytics -- 7.4.4 Telco Company: Building a Data Marketplace -- 7.4.5 Hospital/Faculty of Medicine: Assessing the Organizational Maturity -- 7.4.6 University Library: Assessing the Organizational Maturity -- 7.4.7 DQIoT: Developing a MAMD-Based Maturity Model for IoT -- 7.4.8 Regional Institute of Statistics: Developing a MAMD-Based Model for the Official Statistics Domain -- 7.4.9 CODE.CLINIC: Tailoring MAMD for Coding Clinical Data -- References -- Part II: Data Governance Applied -- Chapter 8: Data Governance in the Banking Sector -- 8.1 Inception, Challenges, and Evolution -- 8.2 Data-Driven Bank -- 8.3 Data Stewardship -- 8.4 Single Data Marketplace Ecosystem (SDM) -- 8.5 DM& -- G Dashboard -- 8.5.1 Overview -- 8.5.2 Forecast -- 8.5.3 Data Value -- 8.6 Data as a Service (DaaS) -- 8.7 The Magic Algorithm -- Chapter 9: Data Has the Power to Transform Society. 9.1 Introduction. |
| Record Nr. | UNINA-9910799479403321 |
| Cham, Switzerland : , : Springer, , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Green in Software Engineering [[electronic resource] /] / edited by Coral Calero, Mario Piattini
| Green in Software Engineering [[electronic resource] /] / edited by Coral Calero, Mario Piattini |
| Edizione | [1st ed. 2015.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 |
| Descrizione fisica | 1 online resource (329 p.) |
| Disciplina |
004
005.1 005.74 338.47004 338.927 658514 |
| Soggetto topico |
Software engineering
Management information systems Computer science Sustainable development Management Industrial management Computer industry Computers and civilization Software Engineering Management of Computing and Information Systems Sustainable Development Innovation/Technology Management The Computer Industry Computers and Society |
| ISBN | 3-319-08581-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Part I Introduction -- 1 Introduction to Green in Software Engineering -- Part II Environments, Processes and Construction -- 2 Green Software Engineering Environments -- 3 Processes for Green and Sustainable Software Engineering -- 4 Constructing Green Software Services: from Service Models to Cloud-based Architecture -- Part III Economic and Other Qualities -- 5 Economic Aspects of Green ICT -- 6 Green Software Quality Factors -- Part IV Software Development Process -- 7 From Requirements Engineering to Green Requirements Engineering -- 8 Towards Green Software Testing -- 9 Green Software Maintenance -- 10 Green Software and Software Quality -- 11 Green Software Measurement -- Part V Practical Issues -- 12 A Decision Making Model for Adopting GreenICT Strategies -- 13 Participation and Open Innovation for Sustainable Software Engineering. |
| Record Nr. | UNINA-9910299235503321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Quantum Software Engineering [[electronic resource] /] / edited by Manuel A. Serrano, Ricardo Pérez-Castillo, Mario Piattini
| Quantum Software Engineering [[electronic resource] /] / edited by Manuel A. Serrano, Ricardo Pérez-Castillo, Mario Piattini |
| Edizione | [1st ed. 2022.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 |
| Descrizione fisica | 1 online resource (321 pages) |
| Disciplina | 004.1 |
| Soggetto topico |
Software engineering
Quantum computers Software Engineering Quantum Computing |
| ISBN | 3-031-05324-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 1 Elías F. Combarro, Quantum Computing Foundations -- 2 Mario Piattini and Juan Manuel Murillo, Quantum software engineering landscape and challenges -- 3 Miguel Ángel Blanco and Manuel Serrano, Quantum Information Technology Governance System -- 4 Benjamin Weder et al., Quantum Software Development Lifecycle -- 5 Carmelo Cartiere, Formal Methods for Quantum Software Engineering -- 6 Carlos A. Pérez-Delgado, A Quantum Software Modeling Language -- 7 Iaakov Exman and Alon Tsalik Shmilovich, Quantum Software Models: Density Matrix for Universal Software Design -- 8 David Valencia et al., Quantum Service Oriented Architectures: from hybrid classical approaches to future standalone solutions -- 9 Antonio García de la Barrera at al., Quantum Software Testing – Current trends & Emerging proposals -- 10 Miguel-Angel Sicilia at al., Quantum software measurement -- 11 Luis Jiménez-Navajas at al., Quantum Software Modernization -- 12 José A. Cruz-Lemus and Manuel Serrano, Quantum software tools overview -- 13 Guido Peterssen at al., Quantum software development with QuantumPath® -- 14 Nir Minerbi, Quantum Software Development with Classiq -- 15 Filipa Ramos Ferreir et al., Quantum Software Frameworks for Deep Learning. |
| Record Nr. | UNINA-9910616389803321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Quantum Software Engineering [[electronic resource] /] / edited by Manuel A. Serrano, Ricardo Pérez-Castillo, Mario Piattini
| Quantum Software Engineering [[electronic resource] /] / edited by Manuel A. Serrano, Ricardo Pérez-Castillo, Mario Piattini |
| Edizione | [1st ed. 2022.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 |
| Descrizione fisica | 1 online resource (321 pages) |
| Disciplina | 004.1 |
| Soggetto topico |
Software engineering
Quantum computers Software Engineering Quantum Computing |
| ISBN | 3-031-05324-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 1 Elías F. Combarro, Quantum Computing Foundations -- 2 Mario Piattini and Juan Manuel Murillo, Quantum software engineering landscape and challenges -- 3 Miguel Ángel Blanco and Manuel Serrano, Quantum Information Technology Governance System -- 4 Benjamin Weder et al., Quantum Software Development Lifecycle -- 5 Carmelo Cartiere, Formal Methods for Quantum Software Engineering -- 6 Carlos A. Pérez-Delgado, A Quantum Software Modeling Language -- 7 Iaakov Exman and Alon Tsalik Shmilovich, Quantum Software Models: Density Matrix for Universal Software Design -- 8 David Valencia et al., Quantum Service Oriented Architectures: from hybrid classical approaches to future standalone solutions -- 9 Antonio García de la Barrera at al., Quantum Software Testing – Current trends & Emerging proposals -- 10 Miguel-Angel Sicilia at al., Quantum software measurement -- 11 Luis Jiménez-Navajas at al., Quantum Software Modernization -- 12 José A. Cruz-Lemus and Manuel Serrano, Quantum software tools overview -- 13 Guido Peterssen at al., Quantum software development with QuantumPath® -- 14 Nir Minerbi, Quantum Software Development with Classiq -- 15 Filipa Ramos Ferreir et al., Quantum Software Frameworks for Deep Learning. |
| Record Nr. | UNISA-996495563203316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||