A software team is building a ride-sharing app. They break the problem into: match riders to drivers, calculate routes, process payments, and send notifications. Which pillar of computational thinking does this represent?

Abstraction Pattern recognition Decomposition Algorithm design

A map-routing algorithm ignores the colour of road signs, the age of bridges, and whether roads pass through scenic areas, focusing only on distance and speed. Which computational thinking pillar does this demonstrate?

Decomposition Abstraction Pattern recognition Algorithm design

You need to find one specific contact in a phone book with 1,000,000 entries sorted alphabetically. Using binary search, approximately how many comparisons are needed in the worst case?

About 500,000 comparisons About 1,000 comparisons About 20 comparisons About 100 comparisons

Binary search requires that the data be sorted before it can be applied. If you have an unsorted list of 10,000 items that you will search only once, which approach is most efficient overall?

Binary search — it is always faster regardless of sort cost Linear search — sorting would cost more than the single search saves Always sort first, as sorted data is generally more useful Hash the data first, then search — this is always fastest

Bubble sort compares adjacent elements and swaps them repeatedly, with time complexity O(n²). Merge sort divides the list, sorts each half, then merges, with time complexity O(n log n). If you need to sort 1,000,000 records, which algorithm is preferable and why?

Bubble sort — it is simpler to implement and thus less error-prone Either algorithm — the difference only matters for very small datasets Merge sort — O(n log n) is dramatically faster than O(n²) at this scale Bubble sort — it uses less memory since it operates in-place

A GPS device calculates a route in under one second for a city with 500,000 road segments. Which category of algorithm enables this, and why is a brute-force approach (checking all possible routes) infeasible?

Sorting algorithms — the road segments are sorted by length in advance Linear search — the GPS checks every road one by one very quickly Graph-search algorithms like A* — brute force has factorial or exponential complexity that would take millennia Binary search — routes are stored in a sorted database

A flowchart uses a diamond shape. What does this symbol represent?

An input or output operation A decision point with two or more possible outcomes (e.g., yes/no) The start or end of the algorithm A process or calculation step

What is the primary advantage of writing pseudocode before writing code in a specific programming language?

It runs faster than compiled code because it skips the compiler It allows the logic to be reviewed and debugged without the distraction of syntax rules It automatically generates working code in any language It is required by law before any commercial software is published

An algorithm that accesses a lookup table and always returns the answer in the same time regardless of how many entries the table has is said to have which time complexity?

O(n) — linear time O(log n) — logarithmic time O(n²) — quadratic time O(1) — constant time

A data compression algorithm used for internet video streaming finds repeated patterns in image frames and stores only the differences between frames rather than complete images. Which computational thinking pillar is most prominent here?

Decomposition Abstraction Algorithm design Pattern recognition

An algorithm that performs well on small datasets suddenly takes hours to run when the dataset size triples. This behaviour is most characteristic of which time complexity?

O(1) — constant time O(log n) — logarithmic time O(n) — linear time O(n²) — quadratic time

Internet routers must forward millions of packets per second to correct destinations. The routing table has thousands of entries. Which search complexity is essential for routers to operate in real time?

O(n²) — routers are powerful enough that complexity does not matter O(n) — linear search is simple and routers are very fast O(1) or O(log n) — linear search O(n) would be too slow at the required throughput O(n log n) — merge sort is used to order packets before forwarding

A well-designed algorithm must be finite. What does this mean, and why is it important?

It must use a fixed amount of memory regardless of input size It must be written in fewer than 100 lines of code It must terminate after a finite number of steps; an infinite loop makes a program unresponsive It must run on finite hardware, so it cannot use cloud servers