Author:
Gryzun Liudmyla,Shcherbakov Oleksandr,Parfonov Yurii,Bodnar Liliia
Abstract
The task of visualization of large graphs as a special data structure and algorithms on them is considered by scientists and practitioners as a complex and non-trivial problem. The analysis of scientific works and existing software applications that implement similar functions of the subject domain testifies the relevance of expanding exploration in the lines of identifying the features of the development of applications for the visualization of large graphs and algorithms on them. The formulation of features and recommendations for the development of such software and presentation of the software module designed by the authors is the aim of the article. In the course of the work, the main features of the development of a program for the visualization of graphs with a large number of vertices were identified and formulated using methods of analysis and graph theory. Special recommendations on the essence of each of the stages of development of such applications were provided and those steps that are most important for developers in terms of the complexity of processing and visualization of large graphs, metrics of their layout in the application screen, etc. were identified. A software module developed by the authors, that provides a unified application programming interface for visualizing any algorithm on graphs, which allows to save time working on utility software and focus more on solving algorithmic problems is also presented. The presented module was developed by the authors taking into account the identified recommendations. A comparative analysis of the developed software module and analogues was carried out, which proved the extended functionality of the module for the visualization of graphs with a large number of vertices. The module is a practically valuable tool for data structures researchers and other experts working on graph algorithms, since it enables data visualization at debugging software and simplifies the analysis of large data structures
Publisher
Scientific Journals Publishing House
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