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Tour Planner Web App

This app was built using Java Spark and Maven for the back-end and React and npm for the front-end. It was deployed to GitHub for releases, automation, workflows, and version control. It is an app that helps users build tours, whether for work or a vacation. Places can be added using the map or the add places button, both explained in detail in the belowe sections. These will appear as their names and display their coordinates in the list below the map. The app also allows you to optimize the tour so there are no overlapping lines and the trip can be efficient. The first location is the starting city and will also be the ending city so the distances are calculated using modulo so the last leg distance is between the last place and the first one. The tests were created using JUnit for unit testing, Jacoco and Jest for coverage testing, and Postman for integration testing.

Using Dijkstra to Route Packages in a Network Overlay

The goal of this project was to use an overlay to communicate between messaging nodes (clients) and the Registry (server) to send messages using threads. It follows the principles of TCP/IP protocols and overlays used in P2P systems. The registry accepts messaging nodes using a server socket and creates receiver and sender threads for that connection. The messaging nodes also have their own sets of threads for the registry and peers. The foreground process in the Registry allows the users to specify commands that creates the undirected graph with all registered nodes, connect to peers to form bidirectional connections, and start sending messages. When all nodes finish messaging each other randomly, the statistics are collected and can be compared to see if any packets were lost during the period.

Distributed_Analytics_of_US_Residential_Zoning

This is a project that aims to do distributed analytics using clusters using a spatial dataset. Our goal with this project was to analyze the impact of single family rresidential zoning in the US and correlate it to quality of life measures in an effort to dissuade a segreggation of zoning types and promote inclusivity. We hoped to be able to compare the results against data from other countries that have more includive zoning laws, but this was not possible due to constraints on data availability and language barriers. For the distributed component, we are using a cluster of 10 machines that are managed by Yarn. To do the processing of data and calculations, we applied Spark using Java and Gradle. The data itself was stored using HDFS and totaled to ~3.2 GB. For more detail on our motivation, procedures, project structure, and results, please reference the latex file or the presentation in the GitHub repo.

Analysis of the MovieLens Dataset using Apache Spark

This project was an introduction to using Apache Spark to analyze a large file (~800 MB), namely the Movie Lens dataset containing movies, genres, ratings, etc. The files were stored using HDFS and cluster size consisted of 10 machines. There is 1 Java file with 7 Spark jobs which are focused on answering the 7 questions that can be found on GitHub.

Analysis of Million Songs Dataset using Hadoop MapReduce

This project was an introduction to using Hadoop MapReduce to analyze a large file (~1.6 GB), namely the Million Song subset containing 10,000 songs. The files were stored using HDFS and cluster size consisted of 10 machines. There are 10 Java files with jobs of their own which are focused on answering the 10 questions below. Please visit the github for more details on the questions, answers, and more.

Fast Multithreaded Matrix Multiplication

This is a very efficient matrix multiplication calculator built using Java and its concurrency libraries. It can be used to multiply matrices populated using a random seed, but it can also be modified to use predefined values. The command line gives you the option to define the size of the matrices, which will be the same for both matrices, the seed used in random to populate the matrices, and the number of threads. The features list below describes the optimizations.

Color Coordinate Generator

This is a color coordinate sheet generator that is actively used in Vision Therapy. The goal was to use web development tags and explore accessibility.

Personal Website

The website you are on! This is my personal website I created using Python's Django framework for the back-end and pure Javascript, HTML, and CSS for the front-end with some help from Bootstrap5. Please feel free to explore the website and the various projects, courses, and features. If you would like to contact me, you can do so using the contact tab or my contact information from the sidebar.

Heuristic Algorithms for Approximating the Traveling Salesman Problem

This program will approximate the Traveling salesman problem using 3 three different algorithms (Nearest Neighbot, 2Opt, and 3Opt). There are size different combinations and explanations for these can be found in the sections below. The program allows you to run each algorithm individually or run a benchmark for all 6 and the original unoptimized list. The results are formatted in a table and displayed in the console. As the algorithms have different time complexities, the time it takes increases for some algorithms drastically, so use caution when using many places.

Great Circle Distance Calculators

This program calculates the distances between coordinates using a possible of three formulas: Vincenty, Cosines, or Haversine. You can choose to use places through the command line or through a file. I would recommend using the file for more than 5 places as it becomes cumbersome to keep adding it through the shell. You can also choose to generate any number of places and then do the calculations.

Infix Expression Calculator

This calculator app utilizes Java and the Swing framework for the calculations and design. Each frame, panel, and component is custom design that is made to look similar in GUI to the calculator offered by Microsoft. It features tons of operations, help menus, an output screen, an operation screen, history tab with details abou the previous calculations, etc. For the actual calculations, it is programmed in Java, so it utilizes most available data structures, sorting algorithms, paring, error handling, etc.

Descriptive Statistics Calculator

This application was inspired by my statistics class, of which one of the chapter was descriptive. In the input screen, you are able to input any number of data values, which are used by the program to calculate and display the descriptive statistics associated with them. The output panel displays the count, frequency of data, min, max, median, IQR, sum, mean, range, variance, and standard deviation. Please look at the images below for reference. This is saved to the history tab each time, which can be clicked on to display all of the statistics in a screen.

CS314: Software Engineering

Introduced team-based development of large, complex systems that supported Scrum-based development while completing a semester-long web development project to prepare for the industry. Topics included clean code, configuration management, continuous integration, testing, requirements, project management and teamwork. The process tools used include Visual Studio Code, IntelliJ IDEA, Linux, Docker, Git, GitHub, Maven, NPM, Webpack, JUnit, Jest, Postman, Zenhub, and Code Climate. The technology tools used include: Linux, Java, JavaScript, ReactJS, Reactstrap, React Leaflet, SQL, MariaDB, Java Spark, Java Concurrency, SLF4J, uLog, JSON, and KML.

CS455: Introduction to Distributed Systems

Covered fundamental ideas and issues in building distributed systems. Examined issues related to concurrent programming, thread pools and safety, non-blocking I/O, scalable server design, file system design, distributed mutual exclusion and deadlock detection, consensus and consistency, pipelining schemes, distributed graph algorithms, distributed shared memory, distributed objects, and MapReduce.

Ayush Adhikari