Time complexity is the amount of time or steps an algorithm takes to complete a task, given a certain input size. It is usually expressed using the big O notation, which describes the upper bound ...

Since the 1970s, algorithms have been able to test graph isomorphism, but in exponential time. This means that the increasing complexity of the graphs increased the algorithm's running time ...

This is a Python application built using the PyQT6 framework to help visualize the time complexity of various algorithms. The user can choose ... You can also adjust the parameters of the graph, such ...

The goal is to leverage parallel computing techniques to optimize the execution time of graph algorithms, leading to improved scalability ... However, the growing size and complexity of real-world ...

Both time and space complexities are discussed. Keywords: weighted spanning trees; enumeration; computational complexity. There are several greedy algorithms for finding a minimal spanning tree M of a ...

In this paper, define several novel time-evolving graph problems and develop algorithms to solve them directly on various, massive, synthetic and real-world time-evolving graphs compressed using our ...

control flow graphs of computer programs. We study efficient algorithms to solve research questions on such networks. One important direction is the use of decomposition techniques to solve problems ...

These days, you get out a computing device, open Google Maps or equivalent, ask it how you should travel somewhere, and most of the time the ... Dijkstra’s algorithm, or the A* graph traversal ...

Big O notation is a mathematical notation that expresses the upper bound of the worst-case scenario of an algorithm's time complexity. It is useful for comparing the efficiency of different ...