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Computer Science Calculators

Free online computer science calculators for algorithms, complexity, data structures, and more.

Amdahl's Law Speedup Calculator

Calculate parallel speedup using Amdahl's and Gustafson's laws. Enter the parallel fraction and processor count to find theoretical maximum speedup.

Bloom Filter False Positive Calculator

Calculate false positive rate of a Bloom filter from bit array size, element count, and hash functions. Includes optimal k recommendation and memory estimate.

Floating-Point Precision Calculator

Compare float16, float32, and float64 precision, range, and machine epsilon. See how many decimal digits each format reliably represents and where rounding errors appear.

Hash Collision Birthday Paradox Calculator

Calculate the probability of a hash collision given hash size in bits and number of values stored. Find how many items trigger a 50% collision chance for any hash width.

Big-O Algorithm Complexity Comparison

Compare operations count for O(1), O(log n), O(n), O(n log n), and O(n²) at any input size. See exactly how fast each complexity class grows.

Binary Search Step Counter

Calculate the maximum and average comparisons binary search needs for any sorted array size. Enter n and see how O(log n) performs versus linear search.

Cache AMAT Calculator

Calculate Average Memory Access Time for a two-level cache hierarchy. Enter L1 and L2 hit times, miss rates, and main memory latency to find AMAT.

Shannon Information Entropy Calculator

Calculate Shannon entropy for up to four symbols. Enter frequencies or counts to find information content in bits, maximum entropy, and coding efficiency.

Download Time Calculator

Estimate how long it takes to download any file at different internet speeds. Enter file size in MB or GB and connection speed to get the result.

RAID Storage Calculator

Calculate usable storage and fault tolerance for RAID 0, 1, 5, 6, and 10. Compare all five configurations side by side for any number of drives.

Master Theorem Calculator

Enter a, b, and d for T(n) = aT(n/b) + O(n^d) to determine Big O complexity. Shows which case applies, the critical exponent, and algorithm efficiency class.

Sorting Algorithm Step Counter

Compare operation counts for bubble, insertion, selection, merge, and quicksort. Enter array size n to see step estimates and Big-O efficiency class.

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