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Preface
The development of computer technology and the popularization of the Internet have made information processing and transmission more efficient, greatly changing the operation methods of finance, commerce, education, entertainment and other fields. Emerging technologies such as data analysis, artificial intelligence and cloud computing are also constantly affecting and changing various industries.
Today, we are witnessing breakthrough developments in artificial intelligence technology. Artificial intelligence technology represented by OpenAI's ChatGPT gives us the opportunity to complete work at the pinnacle of the sum of human knowledge. ChatGPT's powerful text generation capabilities enable us to quickly improve the efficiency of requirements analysis, solution design, and code generation during the software development process. Therefore, we need to re-examine the theory and practice of demand analysis, architecture design, code implementation, software testing, system operation and maintenance and project management in the software development process from the new perspective of ChatGPT, and seriously consider how to use new technological innovations in artificial intelligence working methods and optimize the industrial structure.
"ChatGPT drives software development: AI innovation and practice in the entire software development process"
Written by Chen Bin
IT leader Chen Bin’s new work
Detailed explanation of the application of ChatGPT in the entire software development process
Significantly improve R&D efficiency
Shaping Engineers’ Competitive Advantages in the AI Era
This book comprehensively and in-depth introduces the use of ChatGPT for software product demand analysis, architecture design, technology stack selection, high-level design, database design, UI/UX design, back-end application development, Web front-end development, software testing, system operation and maintenance, Methods and experiences in technical management, etc., with the goal of helping product managers, architects, database administrators, UI/UX designers, programmers, test engineers, operation and maintenance engineers and project managers have a deeper understanding of the practical applications and potential of ChatGPT. and provide them with practical operational advice.
By reading this book, readers can master ChatGPT's core concepts and methods in software product requirements analysis, architecture design, code implementation, system optimization, software testing and team collaboration. This will help software development companies and individuals quickly arm themselves with this powerful tool in the era of artificial intelligence, achieve value innovation and form competitive advantages, laying a solid foundation for future development.
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brief introduction
This is a practical book that explains how large models represented by ChatGPT/GPT-4 can empower the entire life cycle of software development. It takes the full life cycle of software development as the main line and explains in detail the requirements analysis, architecture design, technology stack selection, high-level design, database design, UI/UX design, back-end application development, and Web front-end of ChatGPT/GPT-4 software products. The application scenarios and methods in each link such as development, software testing, system operation and maintenance, and technical management allow readers to deeply feel that ChatGPT/GPT-4 not only innovates traditional software engineering methods and methods, but also brings R&D efficiency and The quality of research and development has been greatly improved.
More importantly, this book can help architects, development engineers, database engineers, test engineers, operation and maintenance engineers, project managers, product managers, UI/UX engineers and technical managers deeply understand the principles of ChatGPT/GPT-4 and applications to comprehensively shape their core competitiveness in the AI era, achieve value innovation and form competitive advantages, laying the foundation for future development.
In this book, the author innovatively proposes a new paradigm for software development in the era of large models - the jellyfish development model (big at the top, small at the bottom). This model divides R&D activities into six levels, corresponding to analysis, design, coding, testing, deployment and maintenance of the software R&D life cycle. Among them, the workload of the analysis and design layers is much larger, similar to the head of a jellyfish; the workload of the remaining four levels is smaller, similar to the tentacles of a jellyfish.
In addition, this book also provides the steps and precautions for engineers to interact with ChatGPT (Prompt). The whole process is divided into 6 steps. As long as you follow these 6 steps, you can easily obtain more satisfactory output results.
About the Author
Chen Bin
Senior technical expert, leader in the field of IT technology, with more than 30 years of experience in payment, software research and development, technical architecture, system operation and maintenance, and technical management. He has in-depth research on artificial intelligence technology and its applications, and has rich practical experience in the application of large models in software engineering. Currently working as the CTO of NetStars, a Chinese payment startup in Japan, he has served as the CTO of Yipay Pay, the senior architect of eBay/PayPal, and the chief engineer of Nokia USA.
Co-chairman of the CTO Leaders Alliance and chairman of the China Internet Technology Committee of 100. He has very rich practical experience from traditional large computer core technology, to Internet technology applications, to big data, cloud computing, biometric identification and financial technology. Efforts have been made to promote the integration of Internet technology and traditional industries. He has participated in many "Internet Caravan" activities and has traveled to traditional enterprises all over China.
He often shares knowledge and experience at Internet industry forums in China, the United States and Japan, and also teaches courses on Internet payment, financial technology and Internet technology management in many well-known universities in China and Japan. He is the author of the best-selling book "Understanding Payment in One Book", and has translated and published many classic works such as "Architecture is the Future", "Architecture Scripture" and "Data is the Future".
Experts recommend
The emergence of ChatGPT is an inevitable result of the development of big data and artificial intelligence to a certain stage. The publication of Mr. Chen Bin's book is very timely. He combines his rich experience in software development and technical management to provide guidance on how to apply ChatGPT in various aspects of software development, such as demand analysis, architecture design, code generation, system optimization, and testing. The suggestions are very helpful for all kinds of IT personnel such as software engineers and product managers, and are worth reading.
—— Liu Zhen, Foreign Academician of the Japan Academy of Engineering/Professor/PhD Supervisor of Nagasaki University of Science and Technology
This book discusses in detail the application of ChatGPT in the software development process, providing a new way to combine AI and software development. This book not only has in-depth theory and explains the working principle of ChatGPT, but is also highly practical, contains a large number of cases, is full of inspiration and wisdom, and covers all possibilities of AI in the field of software development. This is a must-read for anyone interested in AI and software development.
—— Li Gang Founder and Chairman of NETSTARS
Breakthroughs in AI technology have brought new development opportunities to all walks of life, including software research and development. How to make full use of new AI technologies represented by ChatGPT to innovate new models and methods of software development has become an important issue in the software industry. The author explores a new path for software development by summarizing and analyzing the experience and lessons learned from using ChatGPT in software development. If you are interested in using ChatGPT to improve the efficiency of software development, then this book is an indispensable guide.
—— Zhang Yunquan, researcher at the Institute of Computing Technology, Chinese Academy of Sciences/doctoral supervisor/member of the National Committee of the Chinese People’s Political Consultative Conference/deputy director of the 1993 Central Science and Technology Commission
The software industry has always been committed to providing efficient automation tools for humans. However, it is quite ironic that this innovative field still relies heavily on manpower and is a brain-labor-intensive industry. Long time, low efficiency and high cost are the chronic diseases of many software projects. Fortunately, the advent of ChatGPT has brought about unprecedented changes. The efficiency of software development will be greatly improved, and it may even reshape the entire industry. If you are a practitioner in the software industry and are eager to use ChatGPT to lead changes in the software industry, then this book will undoubtedly provide you with valuable guidance and become your right-hand assistant.
—— Xiang Jiangxu, Executive Director of Macau Industrial Technology Research Institute/Managing Partner of Jingcheng Capital
For many years, engineers have been continuously optimizing software development tools to improve software engineering efficiency. The GPT large model is a powerful tool for optimizing software engineering efficiency. Mr. Chen Bin’s understanding of AI technology and rich software engineering experience will greatly promote the application of AI technology in the field of software development. This book expresses obscure technologies in a popular way and is equipped with a large number of cases. It is not only a practical journey of the GPT large model, but also a sublimation of the understanding of the software development process.
—— Zhao Guoguang, Chief Technology Officer of CITIC Cloud Network
Readership
Researchers and development engineers who are interested in ChatGPT and want to apply this advanced technology in actual projects. This book will provide an in-depth analysis of the application of ChatGPT in software development through practical application cases, helping readers quickly master the skills of using ChatGPT to assist software development.
Product managers and designers who want to use ChatGPT to bring value to product innovation and user experience. This book will provide methods and practical cases on how to combine ChatGPT with product design.
A leader is needed to manage and mentor technical teams with technical background related to ChatGPT. They will learn from this book how to organize and coordinate team resources more effectively, as well as how to conduct technology planning and strategic deployment.
Professionals responsible for system operation, maintenance and management of enterprises or projects. In this book, they will learn how to maintain and optimize a ChatGPT-based system to ensure that it operates efficiently and stably.
Teachers, lecturers and students in related majors engaged in artificial intelligence education. They can systematically learn and understand ChatGPT and its application in actual projects by reading this book, providing a reference for teaching and academic research.
General readers who have a strong interest in artificial intelligence and ChatGPT. They can gain a comprehensive understanding of the development history, application fields and future prospects of ChatGPT from this book, and enrich their knowledge system.
Table of contents
Scroll up and down to view the table of contents ↓ Preface
Preface
Chapter 1 ChatGPT and software development 1
1.1 The impact of technological development on software development 1
1.2 ChatGPT’s impact on programming 4
1.3 The impact of ChatGPT on software development model 7
1.4 Jellyfish development model suitable for ChatGPT 13
1.5 The impact of ChatGPT on development engineers 16
1.6 Tips for communicating with ChatGPT 18
1.7 Summary 21
Chapter 2 ChatGPT driver requirements analysis 22
2.1 Use ChatGPT to collect user needs 22
2.2 Use ChatGPT to analyze user needs 28
2.3 Use ChatGPT to optimize user needs 31
2.4 ChatGPT generates requirement specifications 36
2.5 Summary 52
Chapter 3 ChatGPT driver architecture design 54
3.1 The process of architecture design 54
3.2 Introduction to Microservice Architecture 56
3.3 Microservice architecture design principles 58
3.4 Thinking framework of architectural design 58
3.5 ChatGPT generates TMS microservice architecture 60
3.6 Summary 65
Chapter 4 ChatGPT driver technology stack selection 66
4.1 Basic concepts of technology stack 66
4.2 Current mainstream technology stacks and comparisons 67
4.3 Principles for selecting technology stack 69
4.4 TMS technology stack selection 71
4.5 Summary 78
Chapter 5 ChatGPT driver high-level design 79
5.1 Main documents for high-level design 79
5.2 Principles of high-rise design 81
5.3 ChatGPT assists TMS high-level design 81
5.4 Summary 90
Chapter 6 ChatGPT driven database design 91
6.1 Collaboration between database design and ChatGPT 91
6.2 What should be followed when generating database table structure
Principle 92
6.3 Use ChatGPT to complete database design 94
6.4 Use ChatGPT to generate based on data
Database table structure 103
6.5 ChatGPT drives TMS database
Create 107
6.6 Summary 115
Chapter 7 ChatGPT drives UI/UX design 116
7.1 Use ChatGPT to guide UI/UX
Design Principles 116
7.2 Using ChatGPT from a UI/UX perspective
Analyze user needs 118
7.3 Use ChatGPT to complete the TMS interface
Design 128
7.4 Summary 132
Chapter 8 ChatGPT driver back-end application
Development 133
8.1 Backend Overview 133
8.2 Basic concepts of API 135
8.3 API design principles 136
8.4 ChatGPT helps Web API development 142
8.5 ChatGPT helps database API development 143
8.6 ChatGPT generates TMS backend code 145
8.7 Summary 155
Chapter 9 ChatGPT drives Web front-end development 156
9.1 Use ChatGPT to optimize HTML
Structure 156
9.2 Use ChatGPT to improve CSS styles
Effect 159
9.3 Using ChatGPT to speed up JavaScript
Development 162
9.4 Front-end engineering and ChatGPT 166
9.5 ChatGPT assisted front-end testing 169
9.6 Use ChatGPT to improve web accessibility
Accessibility 172
9.7 ChatGPT generates TMS front-end code 175
9.8 Summary 189
Chapter 10 ChatGPT driver software testing 190
10.1 Using ChatGPT to develop a test plan 190
10.2 Using ChatGPT to generate test scenarios 197
10.3 Using ChatGPT to generate test cases 201
10.4 Using ChatGPT to generate test data 207
10.5 Use ChatGPT for defect management and
Regression testing 210
10.6 Using ChatGPT for automated testing
Provide advice 211
10.7 ChatGPT generates test report 212
10.8 Summary 213
Chapter 11 ChatGPT drive system operation and maintenance 214
11.1 ChatGPT in system monitoring
Application 214
11.2 The role of ChatGPT in fault location
Application 217
11.3 ChatGPT’s performance optimization
Application 222
11.4 ChatGPT in vulnerability detection
Application 225
11.5 Summary 228
Chapter 12 ChatGPT driver technology management 229
12.1 Use ChatGPT to generate project management
Plan 229
12.2 Use ChatGPT to develop technical management
Norms and Processes 232
12.3 Using ChatGPT writing and maintenance technology
Document 233
12.4 Using ChatGPT for knowledge management 238
12.5 ChatGPT assists training and skills
Lift 239
12.6 Summary 240
Chapter 13 Ethics and Regulations of ChatGPT 241
13.1 Data privacy and security issues 241
13.2 Ethical principles and responsibilities of artificial intelligence
Belong 243
13.3 Intellectual property rights related to ChatGPT
Protection 245
13.4 Relevant laws, regulations and policy guidance 246
13.5 Summary 247
Chapter 14: Future Prospects of Software Development and
Challenge 248
14.1 The future of software development 248
14.2 Challenges faced by software development 250
14.3 Solutions to future challenges in software development
Measure 252
14.4 Summary 253
Appendix A: Recommended resources and tools 254
Appendix B TMS requirements analysis document 256
Appendix C TMS architecture design document 268
Live broadcast preview
The emergence of GPT not only solves many natural language processing and content generation problems, but also provides new convenience for software development using computer languages. Under the realistic conditions of GPT or AI new technology, what kind of software development model can be used to better improve the efficiency of software development and improve the effect of software development is a question that many people are thinking about.
At 19:00 on Wednesday, November 1, three guests, senior technical expert Chen Bin, Tencent Tech Lead Ru Bingsheng, and President of Nanjing Yunwen Technology NLP Research Institute Du Zhendong shared with you "From Waterfall Model to Jellyfish Model: How ChatGPT empowers Capable of the entire process of software development”
