课程大纲

课程大纲

智能软件工程

课程编码:1801010812I0P1001Y 英文名称:Intelligent Software Engineering 课时:60 学分:3.00 课程属性:学科核心课 主讲教师:罗铁坚

教学目的要求
This course is a basic course for graduate students in computer science and technology. This course focuses on the new issues facing software engineering today and the development of new technologies to address these issues, including requirements engineering, software design, software processes, and software quality. Through this course, students will be able to fully understand the latest developments in software engineering today and enhance the ability to design actual systems.

预修课程
Computer Programming

大纲内容
第一章 Introduction (Week 1) 4.0学时 罗铁坚
第1节 Course contents
第2节 Teaching outcomes
第3节 Competency =[Knowledge+Skills+Disposition]in Task
第4节 Assignment and assessment
第二章 Research Topics (Week 2) 4.0学时 罗铁坚
第1节 The computing theory founders
第2节 Three challenges for creating intelligent system
第3节 Two way to implement intelligent system
第4节 Nine kinds of tasks in developing intellient system
第5节 Exercises
第三章 Domain Problems and Their Scenarios (Weeks 3, 4) 8.0学时 罗铁坚
第1节 Instructional objectives
第2节 Case 1 Operating System and Application Framework (Linux and Ruby on Rail)
第3节 Case 2 Interactive Program Design Environment (Jupyter notebook)
第4节 Case 3 Rubik's Cube Software(Intelligent Robot)
第5节 Case 4 Game of Pond Wars (Intelligent Agent)
第6节 Case 5 Software Version Management and Continuous Integration Platform (GitHub, etc.)
第7节 Exercises
第四章 Business Modeling and Data Modeling (Weeks 5, 6) 8.0学时 罗铁坚
第1节 Instructional objectives
第2节 Domain knowledge and modeling language
第3节 Data format and its representation
第4节 Data relationship and its functions
第5节 Exercises
第五章 Architecture and Application Framework (Weeks 7, 8) 8.0学时 罗铁坚
第1节 Instructional objectives
第2节 Architecture and functionality
第3节 Architecture and data
第4节 Abstract Levels and Knowledge Reuse
第5节 Exercises
第六章 Design Patterns and Code Refactoring (Week 9) 4.0学时 罗铁坚
第1节 Instructional objectives
第2节 Separation of commonality from special functions
第3节 Strategies for dealing with requirements' changes
第4节 Case study
第5节 Exercises
第七章 User Experience and Interface Design (Week 10) 4.0学时 罗铁坚
第1节 Instructional objectives
第2节 Principles of UE and UI
第3节 Information Visulizaiton
第4节 Exercises
第5节 Reading Materials
第八章 Verification and Automated Testing (Week 11) 4.0学时 罗铁坚
第1节 Instructional objectives
第2节 Proof of program correctness
第3节 Software verification methods
第4节 Construct test cases
第5节 Exercises
第九章 System Threats and Prevention (Week 12) 4.0学时 罗铁坚
第1节 Instructional objectives
第2节 Reason about the cause of security events
第3节 Countermesures to stop hacking
第4节 Exercises
第十章 System Scalability and Performance (Week 13) 4.0学时 罗铁坚
第1节 Instructional objectives
第2节 Performance metrics
第3节 Improve performance
第4节 Exercises
第十一章 Continous Integrated Deployment and Services (Week 14) 4.0学时 罗铁坚
第1节 Instructional objectives
第2节 Continuous integration and deployment
第3节 System service and business models
第4节 Exercises

教材信息
1、 Intelligent Systems Design
and Applications
Ajith Abraham,etc. 2022年1月 Springer Nature

参考书

课程教师信息
Tiejian Luo is a professor at the University of Chinese Academy of Sciences and a doctoral tutor. He was the Executive Dean of the School of Information Science and Engineering at the Graduate School of the Chinese Academy of Sciences. He has hosted more than 10 national and corporate research projects, published a total of 112 articlesand a monograph in English. He has more than 30 software copyrights and invention patents. Since 2003, the team leading by him designed and implemented the education cloud of the University of Chinese Academy of Sciences and has been running successfully for more than 10 years. The University of Chinese Academy of Sciences owns all the intellectual property rights of more than 30 application systems (more than 6 million lines of source code) of the cloud platform. In recent years, he has published many academic papers in high level conferences and journals such as AAAI and IEEE Transactions on Cybernetics, and proposed new models for specific problems in natural language understanding and computer vision, and refreshed the accuracy of related public data sets. He received the 2017 Chinese Academy of Sciences Excellent Teacher Award and the first prize of the Excellent Instructor of the National College of Intelligent Intelligence Competition of China Artificial Intelligence Society.