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Algorithms and Computational Thinking Flashcards
Free Computer Science Revision Cards
Work through common algorithms, sorting methods, Big O notation and the principles of computational thinking with these free Computer Science flashcards. Great for GCSE and A Level CS.
Question
What is an algorithm?
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Answer
A finite set of precise, unambiguous instructions to solve a problem or perform a task. Must have a clearly defined start and end, and always produce a result.
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Question
What is computational thinking?
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Answer
A problem-solving approach using four key techniques: decomposition (breaking into parts), abstraction (removing unnecessary detail), pattern recognition, and algorithmic thinking (designing step-by-step solutions).
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Question
What is a flowchart and what symbols are used?
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Answer
A visual representation of an algorithm. Oval = start/end, rectangle = process, diamond = decision (yes/no), parallelogram = input/output, arrow = flow of control.
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Question
What is pseudocode?
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Answer
An informal, plain-English description of an algorithm that resembles code but is not tied to a specific programming language — used to plan logic before coding.
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Question
What is a linear (sequential) search?
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Answer
Checks each item in a list one by one from the start until the target is found or the end is reached. Works on unsorted data. Time complexity: O(n).
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Question
What is a binary search?
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Answer
Searches a sorted list by repeatedly halving the search space — comparing the target to the middle element and discarding half the list each time. Much faster than linear search. Time complexity: O(log n).
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Question
What is a bubble sort?
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Answer
Repeatedly compares adjacent pairs and swaps them if in the wrong order — "bubbling" larger values to the end. Simple but inefficient for large datasets. Time complexity: O(n²).
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Question
What is a merge sort?
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Answer
A divide-and-conquer sort: split the list in half recursively until single elements remain, then merge back in sorted order. More efficient than bubble sort. Time complexity: O(n log n).
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Question
What is an insertion sort?
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Answer
Builds the sorted list one element at a time — takes each element and inserts it into the correct position in the already-sorted portion. Efficient for small or nearly sorted lists. O(n²) worst case.
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Question
What is time complexity and Big-O notation?
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Answer
Time complexity describes how an algorithm's runtime scales with input size. Big-O notation: O(1) = constant, O(log n) = logarithmic, O(n) = linear, O(n²) = quadratic. Lower is better.
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