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🤖 AI & Machine Learning

Data Structures and Algorithms

CMPT 280: Intermediate. This is created by and for the community of students at University of Saskatchewan, Canada

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Data Structures and Algorithms

Sections

1. Lists and Cursors
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4 topics (9 versions)
1.1Array-based lists
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1.2Singly linked list
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1.3Doubly linked lists
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1.4Position in lists: Cursors and Iterators
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2. Regression Testing 1.1
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3 topics (3 versions)
2.1Black-box
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2.2White-box
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2.3Managing expected and unexpected exceptions
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3. Regression Testing 1.2
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3 topics (3 versions)
3.1Black-box
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3.2White-box
2
3.3Managing expected and unexpected exceptions
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4. Testing
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24 topics (24 versions)
4.1Regression Testing
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4.2Good Test Qualities
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4.3Test Cases
4.4Designing Test Cases
4.5Test Case Selection
4.6Black-box Testing
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4.7White-box Testing
4.8Black vs White-box
4.9What Not to Test
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4.10Test Case Best Practices
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4.11Writing Tests in Java
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4.12Testing Return Values
4.13Testing State Changes
4.14Testing Exceptions
4.15JUnit Automation
4.16Mocking in Tests
4.17TDD Basics
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4.18Code Coverage
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4.19CI Integration
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4.20Testing Pitfalls
4.21Testing in Agile
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4.22Data-Driven Testing
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4.23Performance Testing
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4.24Safe Refactoring
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5. Algorithm Timing Analysis
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6. Abstract Data Types and Specification
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7. Trees
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8. Dispensers
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9. Non-keyed Dictionaries
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10. Keyed Dictionaries
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11. Other Trees
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2 topics (4 versions)
11.1Trie Tree
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11.2k-D Tree
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12. Graphs
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4 topics (4 versions)
12.1Directed and Undirected Graphs
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12.2Breadth-First Search
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12.3Depth-First Search
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12.4Shortest Path Algorithms (e.g. Dijkstra’s algoirthm)
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13. Efficient Sorting Algorithms
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5 topics (5 versions)
13.1O(n²) search
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13.2Merge Sort
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13.3Quick Sort
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13.4Heap Sort
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13.5Linear sorts: Bucket, Radix
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