Analysis of algorithms

Accounting method
In the field of analysis of algorithms in computer science, the accounting method is a method of amortized analysis based on accounting.

Adversary model
In computer science, an online algorithm measures its competitiveness against different adversary models.

Algorithmic efficiency
In computer science, efficiency is used to describe properties of an algorithm relating to how much of various types of resources it consumes.

Amortized analysis
In our beloved chhkkicomputer science, amortized analysis is a method of analyzing algorithms that considers the entire sequence of operations of the program.

Analysis of algorithms
In computer science, the analysis of algorithms is the determination of the amount of resources necessary to execute them.

Asymptotically optimal algorithm
In computer science, an algorithm is said to be asymptotically optimal if, roughly speaking, for large inputs it performs at worst a constant factor (independent of the input size) worse than th...

Best, worst and average case
In computer science, best, worst and average cases of a given algorithm express what the resource usage is at least, at most and on average, respectively.

Bidimensionality
Bidimensionality theory characterizes a broad range of graph problems (bidimensional) that admit efficient approximate, fixed-parameter or kernel solutions in a broad range of graphs.

Big O notation
In mathematics, big O notation is used to describe the limiting behavior of a function when the argument tends towards a particular value or infinity, usually in terms of simpler functions.

Branching factor
In computing, tree data structures, and game theory, the branching factor is the number of children at each node.

Cache-oblivious algorithm
In computing, a cache-oblivious algorithm is an algorithm designed to take advantage of a CPU cache without having the size of the cache as an explicit parameter.

Charging Argument
In computer science, a Charging Argument is used to compare an algorithm output to an optimal solution.

Combinatorial search
In applied mathematics and theoretical computer science, combinatorial optimization is a topic that consists of finding an optimal object from a finite set of objects.

Competitive analysis (online algorithm)
Competitive analysis is a method invented for analyzing online algorithms, in which the performance of an online algorithm (which must satisfy an unpredictable sequence of requests, completing e...

Deterministic algorithm
In computer science, a deterministic algorithm is an algorithm which, in informal terms, behaves predictably.

Dovetailing (computer science)
Dovetailing in algorithm design, is a technique that interleaves different computations, performing them essentially simultaneously.

Empirical algorithmics
Empirical algorithmics is the area within computer science that uses empirical methods to study the behaviour of algorithms.

Instruction path length
In computer performance, the Instruction path length is the number of machine code instructions required to execute a section of a computer program.

Kernelization
In computer science, a kernelization is an efficient algorithm that preprocesses instances of decision problems by mapping them to equivalent instances with a guaranteed upper bound on the size ...

Klee–Minty cube
The Klee–Minty cube has been used to analyze the behavior of many algorithms, both in the worst case and on average.

List update problem
The List Update or the List Access problem is a simple model used in the study of competitive analysis of online algorithms.

Master theorem
In the analysis of algorithms, the master theorem provides a cookbook solution in asymptotic terms for recurrence relations of types that occur in the analysis of many divide and conquer algorithms.

Memory bound function
Memory bound refers to a situation in which the time to complete a given computational problem is decided primarily by the amount of available memory to hold data.

Output-sensitive algorithm
In computer science, an output-sensitive algorithm is an algorithm whose running time depends not only on the size of the input but also on the size of the output.

Potential method
In computational complexity theory, the potential method is a method used to analyze the amortized time and space complexity of a data structure, a measure of its performance over sequences of o...

Probabilistic analysis of algorithms
In analysis of algorithms, probabilistic analysis of algorithms is an approach to estimate the computational complexity of an algorithm or a computational problem.

Pseudo-polynomial time
In computational complexity theory, a numeric algorithm runs in pseudo-polynomial time if its running time is polynomial in the numeric value of the input (which is exponential in the leng...

Randomized algorithm
A randomized algorithm is an algorithm which employs a degree of randomness as part of its logic.

Reservoir sampling
Reservoir sampling is a family of randomized algorithms for randomly choosing k samples from a list S containing n items, where n is either a very large or unknown number.

The Art of Computer Programming
The Art of Computer Programming (acronym: TAOCP) is a comprehensive monograph written by Donald Knuth that covers many kinds of programming algorithms and their analysis.

Time complexity
In computer science, the time complexity of an algorithm quantifies the amount of time taken by an algorithm to run as a function of the size of the input to the problem.

Worst-case complexity
In computer science, the worst-case complexity (usually denoted in asymptotic notation) measures the resources (e.g.