C# : Collections
Top 37 C# Example Pages...

[".wsl...rty. [+BiCST~~}T~~YFG776669F+BBCCXBXaBCC_BCCZCBE.BXS}T~~}T~~","Change, coins."," Change is made with a recursive method. This sort of problem, as described in the Structure and Interpretation of Computer Programs, can be solved with recursion.","This implementation"," in the C# language is illustrative. For most of these puzzles, implementing the code yourself (with a little help) is a good way to learn. ","Recursion ","recursion","Example."," This program uses recursion to compute different ways of making change to match a specified amount. Change() will print out all the ways you can make change for a specified amount. ","Example: ","If you specify 51 cents, it will tell you can make this out of 36 1-cent coins and three 5-cent coins.","ins","class","adsbygoogle","data-ad-client","ca-pub-4712093147740724","data-ad-slot","6227126509","data-ad-format","auto","ins","class","adsbygoogle","data-ad-client","ca-pub-4712093147740724","data-ad-slot","6227126509","data-ad-format","auto","Based on:"," .NET 4.5\n\n","C# program that counts change","\n\nusing System;\nusing System.Collections.Generic;\nusing System.Linq;\n\nclass Program\n{\n static void Main()\n {\n List<int> coins = new List<int>();\n List<int> amounts = new List<int>() { 1, 5, 10, 25, 50 };","\n //\n // Compute change for 51 cents.\n //\n ","Change","(coins, amounts, 0, 0, 51);\n }\n\n static void ","Change","(List<int> coins, List<int> amounts, int highest, int sum, int goal)\n {","\n //\n // See if we are done.\n //\n ","if (sum == goal)\n {\n Display(coins, amounts);\n return;\n }","\n //\n // See if we have too much.\n //\n ","if (sum > goal)\n {\n return;\n }","\n //\n // Loop through amounts.\n //\n ","foreach (int value in amounts)\n {","\n //\n // Only add higher or equal amounts.\n //\n ","if (value >= highest)\n {\n List<int> copy = new List<int>(coins);\n copy.Add(value);\n ","Change","(copy, amounts, value, sum + value, goal);\n }\n }\n }\n\n static void Display(List<int> coins, List<int> amounts)\n {\n foreach (int amount in amounts)\n {\n int count = coins.Count(value => value == amount);\n Console.WriteLine(\"{0}: {1}\",\n amount,\n count);\n }\n Console.WriteLine();\n }\n}\n\n","Output: partial","\n\n1: 51\n5: 0\n10: 0\n25: 0\n50: 0\n\n1: 46\n5: 1\n10: 0\n25: 0\n50: 0\n\n1: 41\n5: 2\n10: 0\n25: 0\n50: 0\n\n1: 41\n5: 0\n10: 1\n25: 0\n50: 0\n\n1: 36\n5: 3\n10: 0\n25: 0\n50: 0","Notes, above program."," The 2 List instances declared store the currently recorded values (which starts empty), and the amounts or denominations of coins that are possible to be used. ","List ","list","Int ","int","Note: ","The program emphasizes the recursive Change method. This implements the logic that actually computes the change.","Tip: ","In many recursive methods, it is clearest to add the exit conditions at the start of the function.","Notes, Change method."," Change() first tests for the ideal amount, and if this is reached, it prints it to the screen. It tests to make sure the change collected has not exceeded the target. ","If ","if","Notes, size."," This algorithm only adds coins in increasing size. It starts with the 1-cent coin and continues with the 5-cent coin and then larger coins. The output is automatically sorted.","Output."," Display() prints the frequencies of the coins that can be added together to reach the target value. In the example, all of the output will add up to 51 cents. ","Console.WriteLine ","console","The first output: ","It shows 51 cents being composed of 51 1-cent coins. This is obviously a correct answer.","The second output: ","It shows 51 cents being made up of 46 1-cent coins and one 5-cent coin.","SICP."," The Structure and Interpretation of Computer Programs book uses this example in its first chapter. It counts ways to compute change for 100 cents. See section 1.2.2 Tree Recursion. ","SICP text: mit.edu ","https://mitpress.mit.edu/sicp/full-text/book/book-Z-H-11.html#%_sec_1.2","Answer: ","The answer of 292 is computed from interpreting the Lisp program. On the C# program shown here, you will also get 292 answers.","Also: ","If you modify the program to include a counter, it is clearer that the result is 292.","Performance."," This program is far from ideal for performance. A variety of approaches could be used to transform the process into a faster one. ","Tip: ","You could use arrays instead of List types, and could use a Stack structure instead of a recursive method.","Arrays ","array","Stack ","stack","Performance, continued."," You could improve the loop with a faster algorithm that jumps to the correct starting index based on the current top value. This could be done with a lookup table. ","Foreach ","foreach","A summary."," We wrote an example program that makes change to match a specified amount. It uses a recursive method invocation and the List type to solve a puzzle. ","ins","class","adsbygoogle","data-ad-client","ca-pub-4712093147740724","data-ad-slot","3679700504","data-ad-format","link","ins","class","adsbygoogle","data-ad-client","ca-pub-4712093147740724","data-ad-slot","6227126509","data-ad-format","auto","url(data:image/jpeg;base64,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)","url(data:image/png;base64,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)","url(data:image/png;base64,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)"]

["url(data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAIwAAAB4BAMAAADS7QcCAAAAGFBMVEX////0qHKhmbLDvs74yKT4xaH4yqr2tYUVUWgbAAAAfUlEQVR42u3XsQmAMBgF4V9xAAOCfVxAdAEdQtwg1il0fsHS8IpIsLob4OvPnKy1V7WXWb+J9pQZZpG3zkRNyowmmmBgYGBgYGBgYGBgYGA+Mn0QHTl3V+o1iYieKifLYq4gilnMYqIVBgYGBgYGBgYGBgYG5gfm3ESx0GvePshxrr29cIIAAAAASUVORK5CYII=)","url(data:image/png;base64,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)","url(data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAANMAAABMCAMAAADA6XJ9AAABIFBMVEX/////9Pjcx+np3/L/+PrCotv/8vb/8/f/5u77+Pz/6PD/6/H/7vTfz+z/4+3/6vDQteOsec/17/n/5O3Ijtb/7PL11/CyhNL/5+//6vH/7/XJrN//+/3//f3/+vzv6PXek9/m1/D/+fu4j9W/mNn/4uz/8fXrl9z/6fHWkdvVv+X1nNj/8PX/6/Lzm9nnl93/9/n/5e6zftL/7fP/5e3lld3/8PS0hNL//Pzry+394vT/5OzvmdjDidXtmdzXs+O7hNLTrN//9fjEmNnhk9zQj9n02fH/9fnKotvv3/L11e//9/r//P3/9vj//v743fHx6PX/6O//7/T/7vP34PP67fj12PC6j9X/9vnr3/L/+PvGotv66/neveXmxOrx3vPgo2SoAAAEY0lEQVR4Xu3Z5XLrOBiAYYGRIcgMZeYepmVmvv+7WPtLvHVVNXLH6TRnR++/YvKM6k+2igSFOUMfR9K01knT+3ezZ9txvn+mKW3ENklSMoDBljoK41R1i9CI/3L0SU39xANNIF9gIuC5SV0/0ylwMiZnuSkImYK1M73bZk3aUtNWyEbWzfQq9czifLEpSiVq0jqZ2GV6UU7nXkdRFNbkJw2zyzSmKcCklLIm4PaezgTz4dlR7lkO82FkrvUsh2Xqh7lN6RW0xqbnYCrnNvXARNfaVM5j0pLaAKALU+fgE6ynaXE4AyBJEfoS29fxcLF3fkcRYXI5gIiotWT4BINVmDYZE3fuZUwuunAalnFY8jxvMs+/M/cOGkZpElcyGmefhUwqysZuErVB8evpRW4TAtMYXWjNSsOqJ6x7TB+mdn1h2t2pCk3mOMzmFpt7gHqV1zSao37CeNo8tjdgsbimqlZJTY0cphaDjgqY+tvz9jfzmUg47/Ulxvo0WSyj5Hl8k2VpioJtY8P5XGQaAGREKHVVMAUFTEd7QJqzOmKTWQvTWi5sU0r9MEYpHNMUQY5lN/WD2++e8ra9ILNk4wKm8Dmg5k0cRWRCPUAtCijqfN+IURq6a2ouFF8Y1u5x+kEEP054W8TolrqAKUY9y97D+kOBCfVGYSb1R73ZqDcQx5QujVI6qVvpd4y5i7CVhdLipvCov5eakrDAhExSy6oudcfu8kzpJ7FXKp18l7kcaz3WpGZ3che+p4gJ2tyfm6DhUhPkZsfUN9OvEM/0NYLa8cbreXZmCQhig4vUzP51qgVN0PvTvYXJEpmgQZCu1lvgctZpOFQUzYlJcTqsMIyC1j1vkCaRxa8lxU3QppEulNAEuaMQ+pZvqlilSVq9899Eq5mIjYZsI3Nl50YVMGk5Taj9GkxEaDqByeOmY1xggituZaY2mJycpos3V2AKBCZD69zsAltIaBoRc5Xne1Zi8nOaNIzfwjznm6Y/VHzf0fDw1hg37zWpSQFxeys+s/QfYNKPNfzpEhP3vpt5w9wd6elMw41jPa+JHeNsj2q6zj0jOnZlB+PzJTOimyWZS3cd+CJ9HJOSf+7pzhTjn5fNPXznWaIWIX4qjJpHMbUNMLVzmLo6xvjqFzBFfFPl1xsAAeeAoTBfdldkKs9m+/1+vxy3eXotPi+nqtoihPxWrVYvX54D6Y+u8gZjjslqJiOvM+wqfwKpdu95RBRCQW9+YkhICxV9JkybQIrgmZCtOq1Yh/b9z7l1eyp8zg1CptWaztDDTH/pzoZR8u+Ypg8xmePHNGnoYaa/cXO3XvLumD7s7BY4YylkKu/PMqZrp42Wm2hLzYDOX17pTds68XhnYRXDS0yesaH/IzAx/9ZSSeH7vaN4PvTjykOUK5NSl8RRwSu3leQwU+minEU0mR50xfdG/4dkMplMJpPJBHc5he+GpEmapEmapEmapEmapEmapEmapOmjSppWnzRJkzRJkzRJ07+QCGjGRJDjqAAAAABJRU5ErkJggg==)","url(data:image/jpeg;base64,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)","url(data:image/png;base64,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)","url(data:image/png;base64,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)","url(data:image/png;base64,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)","url(data:image/jpeg;base64,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)"]