{"id":10733,"date":"2023-08-21T18:43:38","date_gmt":"2023-08-21T13:13:38","guid":{"rendered":"https:\/\/www.csestack.org\/?p=10733"},"modified":"2023-08-21T18:46:35","modified_gmt":"2023-08-21T13:16:35","slug":"time-space-complexity-algorithm-program","status":"publish","type":"post","link":"https:\/\/www.csestack.org\/time-space-complexity-algorithm-program\/","title":{"rendered":"Time and Space Complexity of Algorithm or Program Explained"},"content":{"rendered":"\n<p>If you are a computer science student or professional, you must have come across time and space complexity terminologies.<\/p>\n\n\n\n<p>These are two very important fundamental concepts in computer science. These fundamental concepts are very useful <strong>to analyze the efficiency of algorithms and programs<\/strong>.<\/p>\n\n\n\n<p>If you are appearing for a software developer interview, these are the very important concepts you should definitely know.<\/p>\n\n\n\n<p>Let\u2019s check them one by one.<\/p>\n\n\n\n<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_82_2 counter-hierarchy ez-toc-counter ez-toc-custom ez-toc-container-direction\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Table of Contents<\/p>\n<label for=\"ez-toc-cssicon-toggle-item-69fd5b748adef\" class=\"ez-toc-cssicon-toggle-label\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #000000;color:#000000\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #000000;color:#000000\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/label><input type=\"checkbox\"  id=\"ez-toc-cssicon-toggle-item-69fd5b748adef\"  aria-label=\"Toggle\" \/><nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-4'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/www.csestack.org\/time-space-complexity-algorithm-program\/#What_is_Time_Complexity\" >What is Time Complexity?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-4'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/www.csestack.org\/time-space-complexity-algorithm-program\/#What_is_Space_Complexity\" >What is Space Complexity?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-4'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/www.csestack.org\/time-space-complexity-algorithm-program\/#Important_Points_about_Time_and_Space_Complexity\" >Important Points about Time and Space Complexity<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-4'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/www.csestack.org\/time-space-complexity-algorithm-program\/#What_does_O1_time_and_space_complexity_mean\" >What does O(1) time and space complexity mean?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-4'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/www.csestack.org\/time-space-complexity-algorithm-program\/#How_to_choose_an_efficient_algorithm\" >How to choose an efficient algorithm?<\/a><\/li><\/ul><\/nav><\/div>\n<h4 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"What_is_Time_Complexity\"><\/span><strong>What is Time Complexity<\/strong>?<span class=\"ez-toc-section-end\"><\/span><\/h4>\n\n\n\n<p>Time complexity is associated with the time it takes to execute the algorithm.<\/p>\n\n\n\n<p>It measures how the runtime of an algorithm grows as the input size increases.&nbsp;<\/p>\n\n\n\n<p>Big O notation is used to express the time complexity, which provides an upper bound on the growth rate of an algorithm&#8217;s runtime.<\/p>\n\n\n\n<p>Let\u2019s take an example:&nbsp;<\/p>\n\n\n\n<p><strong>If one says, the order of time complexity of the algorithm is O(n) (or O(n^2)), what does it mean?<\/strong><\/p>\n\n\n\n<p>An algorithm with a time complexity of <code>O(n)<\/code> means that the runtime grows linearly with the input size.&nbsp;<\/p>\n\n\n\n<p>An algorithm with <code>O(n^2)<\/code> means that the runtime grows quadratically with the input size, and so on.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"What_is_Space_Complexity\"><\/span><strong>What is Space Complexity<\/strong>?<span class=\"ez-toc-section-end\"><\/span><\/h4>\n\n\n\n<p>Time complexity is associated with the amount of memory space it takes to execute the algorithm.<\/p>\n\n\n\n<p>Space complexity measures the amount of memory an algorithm or program uses as a function of the input size.&nbsp;<\/p>\n\n\n\n<p>Similar to time complexity, it&#8217;s also usually expressed using big O notation.<\/p>\n\n\n\n<p><strong>Let&#8217;s take an example:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>An algorithm with <code>O(n)<\/code> space complexity means that the amount of memory used grows linearly with the input data size.<\/li>\n\n\n\n<li>An algorithm with <code>O(n^2)<\/code> space complexity means that the amount of memory used grows quadratically with the input data size.<\/li>\n<\/ul>\n\n\n\n<h4 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Important_Points_about_Time_and_Space_Complexity\"><\/span>Important Points about Time and Space Complexity<span class=\"ez-toc-section-end\"><\/span><\/h4>\n\n\n\n<ul class=\"wp-block-list\">\n<li>The similarity between time and space complexities is that they are measured against the input data size.<\/li>\n\n\n\n<li>Time and space complexity is not the property of programming language. It is associated with the algorithm.<\/li>\n\n\n\n<li>Usually, space and time complexities are expressed using big O notations.<\/li>\n\n\n\n<li>These two complexities are very beneficial to measure the efficiency of any algorithm.&nbsp;<\/li>\n<\/ul>\n\n\n\n<h4 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"What_does_O1_time_and_space_complexity_mean\"><\/span><strong>What does O(1) time and space complexity mean?<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h4>\n\n\n\n<p>If time complexity <code>O(1)<\/code> means, the algorithm takes constant time irrespective of the input data size. That is, the algorithm is independent of input size.<\/p>\n\n\n\n<p>Similarly, if the space complexity is <code>O(1)<\/code> means, the algorithm takes constant space irrespective of the input data time. That is, the algorithm is independent of input size.<\/p>\n\n\n\n<p>The algorithm that takes constant space and time is the most efficient algorithm.&nbsp;<\/p>\n\n\n\n<h4 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"How_to_choose_an_efficient_algorithm\"><\/span><strong>How to choose an efficient algorithm?<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h4>\n\n\n\n<p>Let\u2019s take an example of <a href=\"https:\/\/www.csestack.org\/different-types-sorting-algorithms\/\">sorting algorithms<\/a> to bring the comparison to the table. There are many sorting algorithms but you have to choose the best one for your project.<\/p>\n\n\n\n<p>If you have a constraint on time execution, you should always choose an algorithm that has low time complexity.&nbsp;<\/p>\n\n\n\n<p>Similarly, if you have a constraint over the memory space, choose an algorithm that has low space complexity.<\/p>\n\n\n\n<p>In case, if you have an algorithm that has both time and space complexity lower than other algorithms, you got the best one.<\/p>\n\n\n\n<p class=\"has-text-align-center\"><strong>Summary<\/strong><\/p>\n\n\n\n<p>Both time complexity and space complexity are crucial for understanding the efficiency of algorithms and programs. <\/p>\n\n\n\n<p>Analyzing these complexities helps developers choose the most appropriate algorithm to solve a specific problem. <\/p>\n\n\n\n<p>Picking the right algorithm for development ensures that software is both performance (time) and resource (memory space) efficient.<\/p>\n\n\n\n<p>I tried to keep it simple. I hope you like this tutorial. If you have any doubts, write down in the comment section below.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>What is Time and Space Complexity of Algorithm? What does O(1), O(n), O(n^2)&#8230; algorithm complexity mean?<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[7],"tags":[2,433],"class_list":["post-10733","post","type-post","status-publish","format-standard","hentry","category-code","tag-code","tag-complexity"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.3 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Time and Space Complexity of Algorithm or Program Explained<\/title>\n<meta name=\"description\" content=\"What is Time and Space Complexity of Algorithm? 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