Code Optimisation Questions
Time complexity refers to the amount of time it takes for an algorithm to run, or the number of operations performed by the algorithm, as a function of the input size. It measures the efficiency of an algorithm in terms of the time it takes to execute.
Space complexity, on the other hand, refers to the amount of memory or space required by an algorithm to run, also as a function of the input size. It measures the efficiency of an algorithm in terms of the space it requires to execute.
In code optimization, time complexity focuses on reducing the number of operations or improving the efficiency of the algorithm to minimize the execution time. This can be achieved by using more efficient data structures, algorithms, or techniques.
On the other hand, space complexity focuses on reducing the memory or space requirements of an algorithm. This can be achieved by optimizing data structures, reducing unnecessary memory allocations, or using techniques like in-place operations.
In summary, time complexity deals with the efficiency of an algorithm in terms of execution time, while space complexity deals with the efficiency in terms of memory or space requirements. Both are important aspects of code optimization and need to be considered to achieve optimal performance.