Computational Thinking · A Beginner’s Guide to Problem-Solving and Programming by Beecher, Karl -- Read -- Imperial Library of Trantor

Index

Front Cover Half Title BCS, THE CHARTERED INSTITUTE FOR IT Title Page Copyright Page Contents List of figures and tables Author Acknowledgements Glossary Introduction: Why Study Computational Thinking? Part I Computational Thinking 1. What is Computational Thinking?

Objectives What is computational thinking? How is computational thinking used? Disclaimers Summary Exercises

2. Logical and Algorithmic Thinking

Objectives Approach Logical thinking Algorithmic thinking ‘Gotchas’ Summary Exercises

3. Problem-Solving and Decomposition

Objectives Where to start Defining the problem Devising a solution: Something to keep in mind Decomposition Other effective strategies Patterns and generalisation Summary Exercises

4. Abstraction and Modelling

Objectives Abstraction Modelling Summary Exercises

5. Anticipating and Dealing with Errors

Objectives Coming to terms with bugs Designing out the bugs Mitigating errors Testing Debugging You can’t have everything: Deciding which errors to fix Summary Exercises

6. Evaluating A Solution

Objectives Solution evaluation Is it correct? Is it efficient? Is it elegant? Is it usable? Trade-offs Summary Exercises

Part II Computational Thinking in Software Development 7. Tutorial for Python Beginners

Objectives Introducing Python First steps Basic types Basic operations Functions Comments Summary Exercises

8. Effective Building Blocks

Objectives Logic Basic algorithmic constructs Program state More advanced constructs Summary Exercises

9. Organising Your Code

Objectives Recap Introducing tkinter Separating concerns Defining information scope Using modules Packages Summary Exercises

10. Using Abstractions and Patterns

Objectives Finding patterns in programs Abstractions in programming Built-in types Creating your own types Ready-made patterns Summary Exercises

11. Effective Modelling

Objectives Recap Entities Relationships Processes Usage General advice Summary Exercises

12. Testing and Evaluating Programs

Objectives Introduction to program testing and evaluation Anticipating bugs Verification and validation Testing the parts Testing the whole Debugging Summary Exercises

13. A Guided Example

Problem definition Problem decomposition Finding patterns Form generalisations and abstractions Models Annotated source code Testing Opportunities for improvement

Appendix A: Reference Lists and Tables

Order of operator precedence Usability heuristics Mutable and immutable types in Python

Appendix B: Answers to Exercises

Notes References Index

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