Free CSP Exam Questions That Helps Candidates Pass

To find the maximum in an unsorted list, the only reliable way is to examine every element once, maintaining the largest seen so far. This takes O(n) time. Option B (binary search) requires a sorted list, which is not guaranteed. Option C adds unnecessary O(n log n) overhead from sorting. Option D is unreliable. Therefore, Option A is correct. CSP emphasizes efficiency analysis using informal Big-O reasoning. Linear scans are optimal for simple aggregation tasks, while sorting or searching strategies are reserved for cases where ordering provides benefit. Choosing the right algorithm depends on problem context and constraints.

Success criteria must be measurable and tied to performance. Reducing wait times by 20% is clear, quantifiable, and testable. Option A is correct. Option B is a design detail, C is a technical choice, and D is aesthetic. CSP emphasizes measurable outcomes to evaluate computational solutions. In this case, metrics like average wait time, throughput, or safety incidents provide objective benchmarks for testing and improving the system.

Ride-sharing apps offer benefits but can also increase traffic by encouraging more vehicles on roads and reducing use of public transport. Option C is correct. Options A, B, and D describe benefits. CSP emphasizes balanced analysis: innovations may solve one problem but create others, requiring thoughtful evaluation of both positive and negative consequences.

Parameters make procedures more general and reusable by accepting different inputs. For example, a function DrawCircle(radius) can be reused for any circle size. Option A is correct. Options B, C, and D are incorrect—parameters don’t guarantee performance, eliminate constants, or prevent bugs. CSP emphasizes procedural abstraction with parameters to promote modularity, reduce duplication, and make programs adaptable.

Insertion sort is efficient on nearly sorted data, often achieving near-linear performance because it makes minimal swaps. Option C is correct. Merge sort is consistently O(n log n) regardless of input order, which may be overkill for nearly sorted lists. Bubble sort is generally inefficient. Random sort is not a valid algorithm. CSP emphasizes analyzing not only efficiency but also suitability for specific input cases. Matching algorithms to problem context is key in computational thinking.