GCSE Computer Science

I. What is an Algorithm?
• A step‑by‑step procedure to solve a problem.
• Represented using pseudocode or flowcharts.

II. Searching Algorithms
• Linear search: O(n), simple but slow.
• Binary search: O(log n), requires sorted data.

III. Sorting Algorithms
• Bubble sort: O(n²), simple.
• Merge sort: O(n log n), efficient.
• Insertion sort: O(n²), good for small lists.

IV. Complexity Analysis
• Big‑O notation: describes time complexity.
• Constant, linear, quadratic, logarithmic.

V. Flowcharts and Pseudocode
• Symbols: start/end, process, decision, input/output.
• Writing pseudocode for algorithms.

VI. Efficiency
• Comparing algorithm efficiency.

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Question 1: How does Insertion sort work?

Question 2: How does Search algorithm work?

Question 3: Why is O(n) important in computer science?

Question 4: How does Trace table work?

Question 5: Give an example of Insertion sort.

Question 6: Explain Algorithm.

Question 7: How does Recursion work?

Question 8: What is Time complexity?

Question 9: How does Bubble sort work?

Question 10: Define Bubble sort.

Question 11: Define O(log n).

Question 12: Define Linear search.

Question 13: Why is Algorithm important in computer science?

Question 14: Give an example of Trace table.

Question 15: Give an example of Efficiency.

Question 16: Explain Binary search.

Question 17: Explain Pseudocode.

Question 18: Give an example of Iteration.

Question 19: Give an example of Flowchart.

Question 20: Give an example of Big-O notation.

💻 GCSE CS