Computational Thinking

Table of contents

1. Front Cover
2. Half Title
3. BCS, THE CHARTERED INSTITUTE FOR IT
4. Title Page
5. Copyright Page
6. Contents
7. List of figures and tables
8. Author
9. Acknowledgements
10. Glossary
11. Introduction: Why Study Computational Thinking?
12. Part I Computational Thinking
13. 1. What is Computational Thinking?
14. Objectives
15. What is computational thinking?
16. How is computational thinking used?
17. Disclaimers
18. Summary
19. Exercises
20. 2. Logical and Algorithmic Thinking
21. Objectives
22. Approach
23. Logical thinking
24. Algorithmic thinking
25. ‘Gotchas’
26. Summary
27. Exercises
28. 3. Problem-Solving and Decomposition
29. Objectives
30. Where to start
31. Defining the problem
32. Devising a solution: Something to keep in mind
33. Decomposition
34. Other effective strategies
35. Patterns and generalisation
36. Summary
37. Exercises
38. 4. Abstraction and Modelling
39. Objectives
40. Abstraction
41. Modelling
42. Summary
43. Exercises
44. 5. Anticipating and Dealing with Errors
45. Objectives
46. Coming to terms with bugs
47. Designing out the bugs
48. Mitigating errors
49. Testing
50. Debugging
51. You can’t have everything: Deciding which errors to fix
52. Summary
53. Exercises
54. 6. Evaluating A Solution
55. Objectives
56. Solution evaluation
57. Is it correct?
58. Is it efficient?
59. Is it elegant?
60. Is it usable?
61. Trade-offs
62. Summary
63. Exercises
64. Part II Computational Thinking in Software Development
65. 7. Tutorial for Python Beginners
66. Objectives
67. Introducing Python
68. First steps
69. Basic types
70. Basic operations
71. Functions
72. Comments
73. Summary
74. Exercises
75. 8. Effective Building Blocks
76. Objectives
77. Logic
78. Basic algorithmic constructs
79. Program state
80. More advanced constructs
81. Summary
82. Exercises
83. 9. Organising Your Code
84. Objectives
85. Recap
86. Introducing tkinter
87. Separating concerns
88. Defining information scope
89. Using modules
90. Packages
91. Summary
92. Exercises
93. 10. Using Abstractions and Patterns
94. Objectives
95. Finding patterns in programs
96. Abstractions in programming
97. Built-in types
98. Creating your own types
99. Ready-made patterns
100. Summary
101. Exercises
102. 11. Effective Modelling
103. Objectives
104. Recap
105. Entities
106. Relationships
107. Processes
108. Usage
109. General advice
110. Summary
111. Exercises
112. 12. Testing and Evaluating Programs
113. Objectives
114. Introduction to program testing and evaluation
115. Anticipating bugs
116. Verification and validation
117. Testing the parts
118. Testing the whole
119. Debugging
120. Summary
121. Exercises
122. 13. A Guided Example
123. Problem definition
124. Problem decomposition
125. Finding patterns
126. Form generalisations and abstractions
127. Models
128. Annotated source code
129. Testing
130. Opportunities for improvement
131. Appendix A: Reference Lists and Tables
132. Order of operator precedence
133. Usability heuristics
134. Mutable and immutable types in Python
135. Appendix B: Answers to Exercises
136. Notes
137. References
138. Index
139. Back Cover