{
 "source": "https://peabody.kids/flashcards/tech-algorithms",
 "id": "tech-algorithms",
 "title": "Algorithms and Big-O",
 "category": "technology",
 "subject": "Computer Science",
 "levels": [
  "9-12",
  "college",
  "adult"
 ],
 "description": "Classic algorithms, how fast they are, and strategies for solving problems.",
 "tags": [
  "algorithms",
  "sorting",
  "searching",
  "Big-O"
 ],
 "frontLabel": "Term",
 "backLabel": "Meaning",
 "cards": [
  [
   "Algorithm",
   "A finite list of steps that solves a problem"
  ],
  [
   "Big-O notation",
   "Describes how running time or memory grows as input grows"
  ],
  [
   "O(1)",
   "Constant time; stays the same as input grows"
  ],
  [
   "O(log n)",
   "Logarithmic time; grows slowly, like binary search"
  ],
  [
   "O(n)",
   "Linear time; grows in proportion to input size"
  ],
  [
   "O(n log n)",
   "Typical of efficient sorting like merge sort"
  ],
  [
   "O(n squared)",
   "Quadratic time; typical of simple nested loops"
  ],
  [
   "O(2 to the n)",
   "Exponential time; becomes huge very quickly"
  ],
  [
   "Time complexity",
   "How running time grows with input size"
  ],
  [
   "Space complexity",
   "How memory use grows with input size"
  ],
  [
   "Linear search",
   "Check each item in order until found; O(n)"
  ],
  [
   "Binary search",
   "Repeatedly halve a sorted list to find an item; O(log n)"
  ],
  [
   "Binary search requirement",
   "The data must be sorted"
  ],
  [
   "Bubble sort",
   "Repeatedly swaps adjacent items that are out of order; O(n squared)"
  ],
  [
   "Selection sort",
   "Repeatedly picks the smallest item and places it first; O(n squared)"
  ],
  [
   "Insertion sort",
   "Builds a sorted list one item at a time; good for small or nearly sorted lists"
  ],
  [
   "Merge sort",
   "Splits the list, sorts the halves, then merges; O(n log n)"
  ],
  [
   "Quick sort",
   "Picks a pivot and partitions around it; average O(n log n)"
  ],
  [
   "Heap sort",
   "Sorts using a heap; O(n log n)"
  ],
  [
   "Pivot",
   "The element used to partition in quick sort"
  ],
  [
   "Stable sort",
   "A sort that keeps equal items in their original order"
  ],
  [
   "Divide and conquer",
   "Split a problem, solve the parts, combine the answers"
  ],
  [
   "Recursion",
   "A function calling itself on smaller input"
  ],
  [
   "Base case",
   "The stopping point of a recursion"
  ],
  [
   "Dynamic programming",
   "Solve overlapping subproblems once and store the results"
  ],
  [
   "Memoization",
   "Caching results of function calls"
  ],
  [
   "Greedy algorithm",
   "Pick the best choice at each step"
  ],
  [
   "Brute force",
   "Try every possibility"
  ],
  [
   "Backtracking",
   "Try choices and undo them when they fail"
  ],
  [
   "Breadth-first search (BFS)",
   "Explore a graph level by level using a queue"
  ],
  [
   "Depth-first search (DFS)",
   "Explore a graph as deep as possible using a stack or recursion"
  ],
  [
   "Dijkstra's algorithm",
   "Finds shortest paths in a weighted graph with non-negative weights"
  ],
  [
   "A* search",
   "A pathfinding algorithm that uses a guess of distance to the goal"
  ],
  [
   "Minimum spanning tree",
   "A tree connecting all nodes with smallest total weight"
  ],
  [
   "Kruskal's and Prim's",
   "Algorithms for finding minimum spanning trees"
  ],
  [
   "Topological sort",
   "Ordering tasks so each comes after its prerequisites"
  ],
  [
   "Hashing",
   "Turning data into a fixed-size number for fast lookup"
  ],
  [
   "Collision",
   "When two keys hash to the same spot"
  ],
  [
   "Euclid's algorithm",
   "Finds the greatest common divisor using repeated remainders"
  ],
  [
   "Sieve of Eratosthenes",
   "Finds all primes up to a number by crossing out multiples"
  ],
  [
   "Fibonacci sequence",
   "Each number is the sum of the two before: 0, 1, 1, 2, 3, 5..."
  ],
  [
   "Factorial",
   "n! is the product of all whole numbers from 1 to n"
  ],
  [
   "Tower of Hanoi",
   "A puzzle that is a classic recursion example"
  ],
  [
   "Traveling salesman problem",
   "Find the shortest route visiting every city once; very hard"
  ],
  [
   "NP-complete",
   "A class of hard problems with no known fast solution"
  ],
  [
   "P vs NP",
   "A famous open question about whether hard-to-solve problems are also easy to check"
  ],
  [
   "Heuristic",
   "A practical shortcut that finds a good answer, not always the best"
  ],
  [
   "Pseudocode",
   "Plain-language description of an algorithm"
  ],
  [
   "Invariant",
   "A condition that stays true during an algorithm"
  ],
  [
   "Best case",
   "The fastest an algorithm can run"
  ],
  [
   "Worst case",
   "The slowest an algorithm can run"
  ],
  [
   "Average case",
   "Typical running time over many inputs"
  ],
  [
   "In-place algorithm",
   "Uses very little extra memory"
  ],
  [
   "Two pointers",
   "A technique using two positions that move through data"
  ],
  [
   "Sliding window",
   "A technique moving a fixed range along data"
  ],
  [
   "PageRank",
   "Google's algorithm that ranks pages by links to them"
  ],
  [
   "Compression algorithm",
   "Makes data smaller, like ZIP or JPEG"
  ],
  [
   "Lossless compression",
   "Compression that can be exactly reversed"
  ],
  [
   "Lossy compression",
   "Compression that discards some data, like JPEG"
  ],
  [
   "Random number generator",
   "An algorithm that makes numbers that look random"
  ],
  [
   "Machine learning algorithm",
   "An algorithm that learns patterns from data"
  ],
  [
   "Al-Khwarizmi",
   "Persian mathematician whose name gave us the word algorithm"
  ],
  [
   "Algorithm origin",
   "Named after a 9th-century scholar al-Khwarizmi"
  ]
 ]
}