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===重构递归===

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Recursive algorithms can be replaced with non-recursive counterparts.<ref>{{cite web| last=Mitrovic| first=Ivan| title=Replace Recursion with Iteration| publisher=[[ThoughtWorks]]| url=https://www.refactoring.com/catalog/replaceRecursionWithIteration.html}}</ref> One method for replacing recursive algorithms is to simulate them using [[memory management|heap memory]] in place of [[stack-based memory allocation|stack memory]].<ref>{{cite web| last=La| first=Woong Gyu| title=How to replace recursive functions using stack and while-loop to avoid the stack-overflow| publisher=CodeProject| date=2015| url=https://www.codeproject.com/Articles/418776/How-to-replace-recursive-functions-using-stack-and}}</ref> An alternative is to develop a replacement algorithm entirely based on non-recursive methods, which can be challenging.<ref>{{cite web| last=Moertel| first=Tom| title=Tricks of the trade: Recursion to Iteration, Part 2: Eliminating Recursion with the Time-Traveling Secret Feature Trick| date=2013| url=http://blog.moertel.com/posts/2013-05-14-recursive-to-iterative-2.html}}</ref> For example, recursive algorithms for [[matching wildcards]], such as [[Rich Salz]]' [[wildmat]] algorithm,<ref>{{cite web| last=Salz| first=Rich| title=wildmat.c| publisher=[[GitHub]]| date=1991| url=https://github.com/trevor/transmission/blob/master/libtransmission/wildmat.c}}</ref> were once typical. Non-recursive algorithms for the same purpose, such as the [[Krauss matching wildcards algorithm]], have been developed to avoid the drawbacks of recursion<ref>{{cite magazine| last=Krauss| first=Kirk J.| title=Matching Wildcards: An Algorithm| magazine=[[Dr. Dobb's Journal]]| date=2008| url=http://www.drdobbs.com/architecture-and-design/matching-wildcards-an-algorithm/210200888}}</ref> and have improved only gradually based on techniques such as collecting [[software testing|tests]] and [[profiling (computer programming)|profiling]] performance.<ref>{{cite web| last=Krauss| first=Kirk J.| title=Matching Wildcards: An Improved Algorithm for Big Data| publisher=Develop for Performance| date=2018| url=http://www.developforperformance.com/MatchingWildcards_AnImprovedAlgorithmForBigData.html}}</ref>

递归算法可以用非递归的对应算法来替换<ref>{{cite web| last=Mitrovic| first=Ivan| title=Replace Recursion with Iteration| publisher=[[ThoughtWorks]]| url=https://www.refactoring.com/catalog/replaceRecursionWithIteration.html}}</ref>。替换递归算法的一种方法是用堆内存代替栈内存来模拟它们<ref>{{cite web| last=La| first=Woong Gyu| title=How to replace recursive functions using stack and while-loop to avoid the stack-overflow| publisher=CodeProject| date=2015| url=https://www.codeproject.com/Articles/418776/How-to-replace-recursive-functions-using-stack-and}}</ref> 。另一种方法是完全基于非递归方法来开发替换算法，这可能是一个挑战<ref>{{cite web| last=Moertel| first=Tom| title=Tricks of the trade: Recursion to Iteration, Part 2: Eliminating Recursion with the Time-Traveling Secret Feature Trick| date=2013| url=http://blog.moertel.com/posts/2013-05-14-recursive-to-iterative-2.html}}</ref> 。例如，用于通配符匹配的递归算法，如Rich Salz的wildmat算法<ref>{{cite web| last=Salz| first=Rich| title=wildmat.c| publisher=[[GitHub]]| date=1991| url=https://github.com/trevor/transmission/blob/master/libtransmission/wildmat.c}}</ref>，曾经是典型的算法。为了避免递归的缺点<ref>{{cite magazine| last=Krauss| first=Kirk J.| title=Matching Wildcards: An Algorithm| magazine=[[Dr. Dobb's Journal]]| date=2008| url=http://www.drdobbs.com/architecture-and-design/matching-wildcards-an-algorithm/210200888}}</ref>，人们开发了用于相同目的的非递归算法，如Krauss通配符匹配算法，并在收集测试和性能分析等技术的基础上逐步改进。<ref>{{cite web| last=Krauss| first=Kirk J.| title=Matching Wildcards: An Improved Algorithm for Big Data| publisher=Develop for Performance| date=2018| url=http://www.developforperformance.com/MatchingWildcards_AnImprovedAlgorithmForBigData.html}}</ref>

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