Computer Science

Algorithms, data structures, complexity, and the theoretical foundations of computing.

Subcategories

• Cryptography — Mathematical techniques for secure communication and data protection.

Articles (19)

• Heaps and Priority Queues: How a Binary Heap Works
  A binary heap stores a priority queue in an array, keeping the smallest item at the top, so each insert and each removal takes logarithmic time, or O(log n).
• The Traveling Salesman Problem: Why the Shortest Route Is Hard
  The traveling salesman problem asks for the shortest route that visits every city once and returns to the start, simple to state but very hard to solve.
• P vs NP
  P vs NP explained: why verifying solutions is easy but finding them may be hard, what polynomial time means, and why this Millennium Prize problem matters.
• Quicksort
  Quicksort explained: how partitioning around a pivot sorts in place, why average-case performance beats merge sort, and when worst-case behavior strikes.
• How ATS Resume Screening Actually Works
  What applicant tracking systems really do to your resume — parsing, knockout questions, ranking — and the formatting and keyword practices that survive them.
• Resume Keywords: Matching Job Descriptions Without Stuffing
  The right way to tailor resume keywords for ATS search — extracting the vocabulary that matters, placing it naturally, and the stuffing patterns that backfire.
• AI in Hiring: Screeners, Rankers, and Your Application
  Where AI actually sits in modern hiring pipelines — resume rankers, assessments, video scoring — what it measures, and how strong candidates adjust without gaming.
• Cover Letter vs Resume: Which One Actually Gets Read?
  What each document is for, which one recruiters actually read first, and how to stop writing two documents that compete with each other.
• Type Theory in Programming Languages
  What a type system actually does — from preventing bugs at compile time to enabling expressive polymorphism — and why type theory underpins modern language design.
• Quantum Computing
  What a quantum computer actually is — qubits, superposition, entanglement, and interference — and which problems it will and will not revolutionize.
• Bellman–Ford Algorithm
  A single-source shortest path algorithm that handles negative edge weights and detects negative cycles, running in O(V×E) time.
• Breadth-First Search
  A graph traversal algorithm that explores vertices in order of distance from a source using a queue, finding shortest paths in unweighted graphs.
• Merge Sort
  A stable O(n log n) divide-and-conquer sorting algorithm that recursively splits an array and merges sorted halves.
• Dynamic Programming
  An optimization technique that solves problems by combining solutions to overlapping subproblems and storing intermediate results to avoid recomputation.
• Hash Tables
  A data structure that stores key–value pairs with expected constant-time insertion, lookup, and deletion.
• Dijkstra's Shortest Path Algorithm
  A greedy graph algorithm that finds the shortest paths from a single source vertex to all others in graphs with non-negative edge weights.
• Binary Search
  An algorithm that locates a target in a sorted array in logarithmic time by repeatedly halving the search interval.
• Big O Notation
  A notation for describing how an algorithm's runtime or memory usage grows as the input size increases.
• Regular Expressions
  A compact pattern language for matching and transforming text, grounded in the theory of finite automata.

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