Computational resources

Scalability is the property of a system to handle a growing amount of work. One definition for software systems specifies that this may be done by adding resources to the system.

estimate of time taken for running an algorithm

measure of the amount of resources needed to run an algorithm or solve a computational problem

In computational complexity theory, DTIME (or TIME) is the computational resource of computation time for a deterministic Turing machine. It represents the amount of time (or number of computation steps) that a "normal" physical computer would take to solve a certain computational problem using a certain algorithm. It is one of the most well-studied complexity resources, because it corresponds so closely to an important real-world resource (the amount of time it takes a computer to solve a problem).

amount of memory space that an algorithm uses as a function of the input's size

In computational complexity theory, the complexity class 'NTIME(f(n))' is the set of decision problems that can be solved by a non-deterministic Turing machine that runs in time O(f(n)), where O is the big O notation, f is some function, and n is the size of the input (for which the problem is to be decided).

In computational complexity theory, DSPACE or SPACE is the computational resource describing the resource of memory space for a deterministic Turing machine. It represents the total amount of memory space that a "normal" physical computer would need to solve a given computational problem with a given algorithm.

In computational complexity theory, non-deterministic space or NSPACE is the computational resource describing the memory space for a non-deterministic Turing machine. It is the non-deterministic counterpart of DSPACE.

abstraction in a computational model describing a kind of computer resource an algorithm uses

the phenomenon where a program doesn't properly release resources like memory, file handles, or sockets, causing them to remain occupied in vain (leading to potential issues like performance degradation, crashes, or data loss)