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E-raamat: Knowledge Driven Development: Bridging Waterfall and Agile Methodologies

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  • Formaat: PDF+DRM
  • Sari: Cambridge IISc Series
  • Ilmumisaeg: 12-Jul-2018
  • Kirjastus: Cambridge University Press
  • Keel: eng
  • ISBN-13: 9781108681407
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Knowledge Driven Development: Bridging Waterfall and Agile MethodologiesSuurem pilt
  • Formaat: PDF+DRM
  • Sari: Cambridge IISc Series
  • Ilmumisaeg: 12-Jul-2018
  • Kirjastus: Cambridge University Press
  • Keel: eng
  • ISBN-13: 9781108681407
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This book presents a new methodology, known as Knowledge Driven Development, for managing project knowledge in an exhaustive and structured manner. The text highlights the importance of efficient project delivery methodology in the overall software development life cycle. Important topics such as requirement analysis, solution design, application design, and test design are discussed in depth. It establishes a connection between enterprise knowledge and project knowledge for continuous improvement and accelerated project delivery. Separate chapters on end-to-end project delivery, compliance and protocols and interface with existing methodologies makes it useful for the readers. Several case studies and examples are interspersed throughout the text for better understanding.

Useful text in the field of computer science, providing a different methodology in the project knowledge management domain for keeping the documents updated. The methodology known as Knowledge Driven Development is exhaustive, structured and flexible as compared to other techniques.

Arvustused

'This book introduces a new software development methodology - Knowledge Driven Development (KDD) based on digitisation of the project knowledge Via 17 chapters of the book, the author has provided the full conceptual details of KDD and GKMF [ Generic Knowledge Management Framework] to be assessed by interested readers in industry and academia. This book adds to the existing literature on software engineering and knowledge management.' IEEE India Council Newsletter

Muu info

Provides detailed methodology for digitizing project knowledge by bridging the gap between Waterfall and Agile Methodologies.
Figures
xi
Tables
xiii
Foreword xv
Preface xix
Acknowledgements xxiii
Overview of the Book xxv
1 Knowledge Driven Development: What is the Proposition?
1(29)
1.1 Knowledge Driven Development (KDD): A Background
1(8)
Overview
4(1)
1.2.1 Waterfall Methodology
4(1)
1.2.2 Agile Methodology
5(1)
1.2.3 KDD Methodology
5(4)
1.3 Case Study: Customer Self-Service
9(17)
1.3.1 Implementation using Waterfall methodology
10(4)
1.3.2 Implementation using Agile Methodology
14(4)
1.3.3 Implementation using KDD Methodology
18(8)
1.4 Difference in Approach among Waterfall, Agile and KDD
26(4)
2 Project Delivery and Supporting Methodologies
30(16)
2.1 IT Industry from Technology and Domain Perspective
30(2)
2.2 Information Technology: A Knowledge-Based Industry
32(2)
2.3 IT Project Delivery: An Introduction
34(4)
2.4 IT Project Delivery Methodology Landscape
38(8)
3 Project Delivery Pain Areas and the Way Forward
46(13)
3.1 Context
46(2)
3.2 IT Project Failures
48(2)
3.3 Project Delivery Pain Areas
50(2)
3.4 Project Knowledge
52(7)
4 Project Knowledge Model: Context and Definition
59(38)
4.1 Traditional Project Knowledge Management
59(3)
4.1.1 Project Knowledge Management in Waterfall Methodologies: Document Driven
60(1)
4.1.2 Project Knowledge Management in Agile Methodology: Collaboration Driven
61(1)
4.2 Project Delivery Activities and Project Knowledge
62(6)
4.2.1 Project Delivery Activities
62(1)
4.2.2 Activities Mapped to End-to-End Project Delivery
63(3)
4.2.3 Project Delivery Activities: Inherent Interactions
66(2)
4.3 Project Knowledge Model: Definition
68(25)
4.3.1 Knowledge Evolution and Project Knowledge
68(3)
4.3.2 Software Project Knowledge Building Blocks
71(5)
4.3.3 Project Knowledge Building Blocks Mapped to Knowledge-Intensive Phases
76(1)
4.3.4 Project Knowledge: Away from Documents and towards a Model
76(9)
4.3.5 Project Knowledge Model Defined
85(8)
4.4 Project Knowledge Model: An Example
93(4)
5 Project Knowledge Model: A Differentiator
97(24)
5.1 Project Knowledge Model Characteristics: Traceability and Flexibility
97(1)
5.2 Advantages of the Project Knowledge Model
98(20)
5.3 Reason for Delay in Discovering Project Knowledge Model
118(1)
5.4 What Does it Really Mean for Project Delivery?
119(2)
6 Project Knowledge Model vs Project Documents
121(19)
6.1 Project Knowledge Model and Project Documents
121(4)
6.2 Comparison of Project Knowledge Model and Project Documents
125(7)
6.3 Document Excerpt and Equivalent Project Knowledge as per the Project Knowledge Model
132(4)
6.4 Output of Project Knowledge Model
136(4)
7 Extending Project Knowledge Model to Cover End-to-End Project Delivery - KDD
140(29)
7.1 Introduction
140(1)
7.2 KDD Focus Area
141(1)
7.3 KDD Core Values
142(11)
7.4 End-to-End Project Delivery Using Quality Gate
153(11)
7.5 Tracking Project Delivery Quality via Key Performance Indicators (KPI)
164(3)
7.6 Fitment for Different Types of Domains and Projects
167(1)
7.6.1 Domain Relevance
167(1)
7.6.2 Project Type Relevance
167(1)
7.7 KDD differentiators
167(2)
8 Extended KDD: Pre-Requirement and Post Delivery
169(3)
8.1 Business Case (Pre-Requirement)
169(1)
8.2 Service Management (Post Delivery)
170(2)
9 KDD Compliance with Standards of Project Delivery
172(26)
9.1 Quality Assurance Framework
172(8)
9.1.1 Six Sigma
173(2)
9.1.2 CMMI
175(5)
9.2 Project Management Framework
180(7)
9.2.1 PMP
180(4)
9.2.2 PRINCE2
184(3)
9.3 Service Management Framework
187(1)
9.4 Enterprise Architecture Framework
187(6)
9.4.1 TOGAF
188(1)
9.4.2 Zachman Framework
189(4)
9.5 Business Analysis Framework
193(1)
9.6 Test Management Framework
194(4)
10 Enabling DevOps
198(5)
10.1 What Is DevOps
198(1)
10.2 DevOps Focus Area and Assistance by KDD
199(4)
11 Addressing Contemporary Concerns of Project Delivery
203(11)
11.1 Shift Left
203(2)
11.2 Knowledge Management
205(4)
11.3 Digitisation
209(1)
11.4 Collaboration
209(1)
11.5 Agile Way of Working
209(1)
11.6 Systems Thinking
210(1)
11.7 Lean Way of Working
211(1)
11.8 Software Engineering Modelling
211(1)
11.9 Machine Learning and Artificial Intelligence
211(1)
11.10 Internet of Things (IOT)
212(2)
12 Helping Existing Methodologies
214(6)
13 Technology Enablers: Tools and Automation
220(13)
13.1 Automation Potential in Project Delivery
220(3)
13.2 Tools Landscape in Project Delivery Environment and PKM
223(3)
13.3 PKM: Conceived as ALM Plus Enterprise Knowledge Management
226(2)
13.4 Benefits of Automation
228(5)
14 Suits Factory Model: Needs Cultural Change
233(8)
14.1 Bringing IT Project Delivery Closer to Process-Based Industry
233(2)
14.2 Implementing the Factory Model
235(3)
14.3 The Need for Cultural Change
238(3)
15 Global Relevance of KDD: GKMF Assisting Skill Development
241(16)
15.1 KDD and Generic Knowledge Management Framework
241(4)
15.2 Examples of Generic Knowledge Management Framework
245(3)
15.2.1 Password Management in IT Industry
245(2)
15.2.2 Plantation: Agriculture
247(1)
15.3 Generic Knowledge Management Framework: Used in Skill Development
248(8)
15.3.1 Portal Development
249(3)
15.3.2 Insurance Industry
252(2)
15.3.3 Agriculture Industry
254(2)
15.4 Towards Another Ontology Framework
256(1)
16 Lean KDD: Elimination of Requirement and Test Design?
257(4)
16.1 Revisiting KDD: Elimination of Test Design Phase
257(1)
16.2 Influence of Business Rule and Scenario on Project Delivery
258(1)
16.3 Lean KDD: without Requirement and Test Design
259(2)
17 Conclusion
261(4)
Appendix A Illustrative Non-Functional Attributes 265(2)
Appendix B Compliance of PKM with GKMF 267(5)
Appendix C Project Estimate and Business Rule/Scenario Framework 272(2)
Appendix D Inventory Relationship for Setting up of Security Questions - as per Example in
Chapter 6		 274(7)
Appendix E KDD: Response to Criticism 281(5)
Glossary 286(4)
References 290(3)
Index 293
Manoj Kumar Lal completed his post-graduation in Aerospace engineering from the Indian Institute of Science, Bangalore in 1997. He joined Tata Consultancy Services in 1997 and has spent twenty years in the organization. He has worked extensively in the field of IT project delivery with specialization in business analysis and quality assurance. His area of interest is software engineering and digitization of knowledge.
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