An algorithm can terminate after a finite number of steps and in a finite amount of time.

①Every instruction in the algorithm must have an exact meaning without ambiguity. ②Under any conditions, there is only one execution path. That is, for the same input, the same output must be produced.

The operations described in the algorithm are feasible. The described operations in the algorithm can be realized by a finite number of operations of the implemented basic operations.

An algorithm has zero or more inputs.

An algorithm has one or more outputs.

①Correctness refers to the absence of grammatical errors. ②The accuracy should be able to meet the requirements of specific problems and correctly reflect the needs.

①Readability refers to how easy it is for people to read the algorithm. ②Good readability helps people understand the algorithm.

① Robustness mainly refers to the ability to handle errors or abnormal situations. ②When the input data is illegal, the algorithm can handle it appropriately instead of producing inexplicable output results.

①Efficiency describes the execution time of the algorithm, and storage capacity refers to the maximum storage capacity space required during the execution of the algorithm. ② It requires as little time as possible and as low storage requirements as possible.

①The most important basis for evaluating the quality of a program algorithm is how much machine resources the program takes up during its execution. Among various machine resources, the most important ones are time resources and space resources. ② Therefore, when analyzing a program, the most important thing everyone is concerned about is the time cost of the algorithm used in the program when it is running and the space cost occupied by the data structures used in the program. ③In other words, time complexity and space complexity are usually used to measure the efficiency of an algorithm.

space complexity

time complexity