This textbook is intended as a textbook for one-semester, introductory computer science courses aimed at undergraduate students from all disciplines. Self-contained and with no prerequisites, it focuses on elementary knowledge and thinking models. The content has been tested in university classrooms for over six years, and has been used in summer schools to train university and high-school teachers on teaching introductory computer science courses using computational thinking. This book introduces computer science from a computational thinking perspective. In computer science the way of thinking is characterized by three external and eight internal features, including automatic execution, bit-accuracy and abstraction. The book is divided into chapters on logic thinking, algorithmic thinking, systems thinking, and network thinking. It also covers societal impact and responsible computing material - from ICT industry to digital economy, from the wonder of exponentiation to wonder of cyberspace, and from code of conduct to best practices for independent work. The book's structure encourages active, hands-on learning using the pedagogic tool Bloom's taxonomy to create computational solutions to over 200 problems of varying difficulty. Students solve problems using a combination of thought experiment, programming, and written methods. Only 300 lines of code in total are required to solve most programming problems in this book.

This book constitutes the refereed proceedings of the 40th National Conference on Theoretical Computer Science, NCTCS 2022, held in Changchun, China, during July 29-31, 2022. The 13 full papers and 6 short papers included in this book were carefully reviewed and selected from 58 submissions. They were organized in topical sections as follows: computational theory and model; approximation algorithms; artificial intelligence; and system and resource scheduling.

This textbook is intended as a textbook for one-semester, introductory computer science courses aimed at undergraduate students from all disciplines. Self-contained and with no prerequisites, it focuses on elementary knowledge and thinking models. The content has been tested in university classrooms for over six years, and has been used in summer schools to train university and high-school teachers on teaching introductory computer science courses using computational thinking. This book introduces computer science from a computational thinking perspective. In computer science the way of thinking is characterized by three external and eight internal features, including automatic execution, bit-accuracy and abstraction. The book is divided into chapters on logic thinking, algorithmic thinking, systems thinking, and network thinking. It also covers societal impact and responsible computing material - from ICT industry to digital economy, from the wonder of exponentiation to wonder of cyberspace, and from code of conduct to best practices for independent work. The book's structure encourages active, hands-on learning using the pedagogic tool Bloom's taxonomy to create computational solutions to over 200 problems of varying difficulty. Students solve problems using a combination of thought experiment, programming, and written methods. Only 300 lines of code in total are required to solve most programming problems in this book.

This book constitutes the thoroughly refereed proceedings of the 39th National Conference of Theoretical Computer Science, NCTCS 2021, held in Yinchuan, China, in July 2021. The 67 full papers were carefully reviewed and selected from 145 submissions, and 14 of them were selected for the volume. The papers present recent research in the areas of information hiding, data detection and recognition, system scheduling, time series prediction, and formal analysis.

This volume constitutes the proceedings of the 13th International Conference on Algorithmic Aspects in Information and Management, AAIM 2019, held in Bejing, China in August 2019. The 31 full papers presented were carefully reviewed and selected. The papers deal with most aspects of theoretical computer science and their applications. Special considerations are given to algorithmic research that is motivated by real-world applications.