![]() However, since April 2022, a mobile (lite) version of VisuAlgo has been made available, making it possible to use a subset of VisuAlgo features on smartphone screens. For an optimal user experience, a minimum screen resolution of 1366x768 is recommended. Initially, VisuAlgo was not designed for small touch screens like smartphones, as intricate algorithm visualizations required substantial pixel space and click-and-drag interactions. While primarily designed for National University of Singapore (NUS) students enrolled in various data structure and algorithm courses (e.g., CS1010/equivalent, CS2040/equivalent (including IT5003), CS3230, CS3233, and CS4234), VisuAlgo also serves as a valuable resource for inquisitive minds worldwide, promoting online learning. Suhendry Effendy - VisuAlgo remains the exclusive platform for visualizing and animating several of these complex algorithms even after a decade. Steven Halim's book, 'Competitive Programming' - co-authored with Dr. Set_minheap.erase( *set_minheap.Initially conceived in 2011 by Associate Professor Steven Halim, VisuAlgo aimed to facilitate a deeper understanding of data structures and algorithms for his students by providing a self-paced, interactive learning platform.įeaturing numerous advanced algorithms discussed in Dr. Std :: cout << *set_minheap.cbegin() << " " Std :: cout << "Elements in min heap : " Std :: cout << "Biggest element : " << *set_minheap.crbegin() << std :: endl Std :: cout << "Smallest element (root) : " << *set_minheap.cbegin() << std :: endl Std :: cout << " \n\n Min Heap using set." << std :: endl Std :: cout > set_maxheap (vec_nums.cbegin(), vec_nums.cend()) #include #include #include class Mountain Removing the element in the heap ( min or max ) takes O ( log n ) time. Any element of the heap created using set can be removed. Removing the element at the top of heap ( min or max ) takes O ( log n ) time. Only the element at the top of the heap created using priority_queue can be removed. Thus any element of a heap can easily be searched for. ![]() Any element of the set can be found in O ( log n ) time. As a priorty_queue does not support find operation, an element in a heap ( min or max ) cannot be searched for. ![]() The biggest element at the top and the smallest element can be accessed in O ( 1 ) time using forward and reverse iterators respectively. Accessing the element at the top of the heap ( min or max ) takes O ( 1 ) time using. Inserting into a heap ( min or max ) created using set takes O ( log n ) time. Inserting into a heap ( min or max ) created using priority_queue takes O ( log n ) time. Each element of a set is allocated its own memory. Set is implemented as a BST ( binary search tree ). Priority_queue uses a std :: vector as default underlying storage for storing the elements. Min / Max heap using std :: priority_queue Max Heap and Min Heap could easily be implemented in C++ using priority_queue or set. Similarly, Min Heap is also a tree-based data structure in which the key of the parent node is less than or equal to the keys of its children. Max Heap is, in essence, a tree-based data structure in which the key of the parent node is greater than or equal to the keys of its children. C++ : Max Heap / Min Heap Using Priority Queue & Set
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