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4 gru 2011 · With C++11 for measuring the execution time of a piece of code, we can use the now() function: auto start = std::chrono::steady_clock::now(); // Insert the code that will be timed auto end = std::chrono::steady_clock::now(); // Store the time difference between start and end auto diff = end - start;
23 gru 2009 · I want to test which data structure is the best by looking at the run-time performance of my algorithm, how do I do it? For example I already have a hashmap<string, int> hmp ; assuming I have "apple" in my hashmap I want to know how long the following statement takes to execute: hmp["apple"] .
In this article, we learn how to estimate the running time of an algorithm looking at the source code without running the code on the computer. The estimated running time helps us to find the efficiency of the algorithm.
For example, the running time of the statement “y = a[i]” is 3t fetch + t store +t []. The fetches are (1) the value of i, (2) the value of a and (3) the value of a[i]. Using these rules, we can easily estimate the running time of the algorithms. Examples. Here, we present some programs in C++ and we estimate their running time.
Running Time It is convenient to use a function T(n) to represent the number of units of time taken by a program or an algorithm on any input of size n. We shall call T(n) the running time of the program. For example, a program may have a running time T(n) = cn, where c is some constant. Put another way, the running time of this
To calculate the running time of an algorithm, you have to find out what dominates the running time. For example, if you've designed an algorithm which does binary search and quick sort once, it's running time is dominated by quick sort.
Analysis of Algorithm 10 Estimating Running Time Algorithm arrayMax executes 6n −2 primitive operations in the worst case Define a Time taken by the fastest primitive operation b Time taken by the slowest primitive operation Let T(n) be the actual worst -case running time of arrayMax. We have a (6n −2) ≤T( ) b 2) Hence, the running time T ...
