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2 - Analysis
Problem Solving with Algorithms and Data Structures(Python)
Question | Answer |
---|---|
average case | algorithm performs somewhere in between these two extremes |
Big-O notation | order of magnitude; used to compare efficiency of algorithms |
brute force | technique for solving a problem typically tries to exhaust all possibilities |
checking off | to determine and keep track of whether certain conditions are met by multiple pieces of data |
exponential | O(2^n); function that grows extremely fast |
linear | O(n); polynomial of degree one; straight line |
log linear | O(n log n); a function whose growth is somewhere between logarithmic and quadratic |
logarithmic | O(log n); slowest growing function |
order of magnitude | a function that describes the part of T(n) that increases the fastest as the value of n increases |
quadratic | O( n^2 ); polynomial of degree one |
time complexity | refers to the amount of time it takes an algorithm to run; represented in Big-O notation. |
worst case | refers to a particular data set where the algorithm performs especially poorly |