Most of the Algorithm visualisation projects deliver an abstract visualization where the main criteria would be to analyze the performance of an algorithm. But we wanted to focus on delivering a learning experience to the student.
It was not easy to implement bubble sort. Visualizing it as taught in the classroom made it hard to implement. But it became easy once we made designs beforehand on how the entire visualization must look.
Merge Sort was the Hardest of all. It took a long time to code it as it contains a lot of steps in the visualization and required a lot of debugging. But we made it through by using setTImeout(Func(), millisec) function which executed each step at a specified time. You can look at the code here.
We wanted to make the visualizations to be more than just mere animations. So we added the algorithm trace while the visualization is running to provide the exact step of algorithm that is being visualized.
We were having a course "Data Mining" while we were doing the project. And we thought it would be awesome if we visualize one of the algorithms explained in the course. We found out that there was an awesome visualization already done and it was open source. So we integrated it into our project and customized it accordingly.
Mr.Prasad Shiva was fascinated by the project. He forked the Algovis repository in the Github and modified existing Bubble sort and made Optimized Bubble Sort visualization out of it. He made a pull request and we merged the pull request.
As our motto goes "Anything is easy to learn if it is visually presented in a simple way. So we will strive to make learning simple and more exciting". So we created various cheatsheets and uploaded them onto the site.
Our website didn`t work correctly with Firefox and other browsers. But we decided to make it right by working on Major changes to the project and making it cross-browser compatible. We also moved from the old theme to an exciting new Dark theme. And accordingly, many other changes were made.
We wanted to even add some of the data we collected for analyzing career trends to the project. So we created a datasets section where we host the public datasets which are created by the data collected by us.
Mr. Sri Pravan Paturi forked the Algovis Repo and Jekyllified the site in order to make the development of future builds easy. And also based on a survey 90% were happy with the dark theme but, the rest of 10% wanted a white theme. So we Added the option to shift themes.
We developed and added Local Binary Pattren Visualization. This was rather an easy one to do, but it may be useful.
Insertion Sort Visualization is added and this is by far the most complex visualization developed. You can see the visualization code in here