My name is Anthony Baratti, and I am a Software Engineering Student at Southern New Hampshire University (2022-2025).
I have studied Client-Server Development, Data Structures & Algorithms, Emerging Technologies (Artificial Intelligence), Full Stack Development
(MongoDB, Express, AngularJS, and Node.js) & Cloud Deployment (Docker and AWS), Secure Coding Principles, Mobile Architecture & Application Development, System Analysis & UI/UX Design,
Reverse Engineering, Testing, Computer Graphics (OpenGL), and Micro-Controller Programming (state machine).
I have used Java, Python, C/C++, JavaScript, TypeScript, and have used JSON and SQL modeling to create and manage databases in MongoDB, AWS, and
SQLite3 with knowledge of tools such as Postman and MongoDB Compass.
I have used Eclipse, PyCharm, Jupyter Notebook, Spyder, Microsoft Visual Studio, Visual Studio Code, Android Studio, among many other IDEs. I have developed
cloud services using the AWS platform, using S3, Lambda Functions, and API Gateways.
During my academic career at Southern New Hampshire University, applying best practices was a critical foundation for success. Detailed commenting and
documentation, thorough unit testing, UI and UX design (including platform-specific mobile and wearable design), diagram design and completeness,
developing a security mindset (such as defense by design, layered defense, principle of least privilege, OWASP dependency checks, etc.),
modularity (separation of concerns), portability (building re-usable components), scalability, determining best architectures, planning and pseudocode,
and much more. Combining all of these skill sets has allowed me to practice not just productive coding but has honed those skill sets into well-rounded
and versatile tools that can be applied to add value to software engineering and development. Reading and writing code became second nature as the ability
to plan and construct robust systems with complete documentation and functionality paved the foundation for excellence.
Object-oriented programming (OOP) created an environment in which principles such as encapsulation, inheritance, abstraction, and polymorphism
(such as method overloading) allowed for a creative mix of problem-solving solutions that helped construct dynamic and reusable code.
Discovering a plethora of libraries such as Python’s NumPy, Pandas, Keras, and TensorFlow backend, Java’s Spring Framework and JUnit testing framework,
JavaScript with Node.js framework such as Express and React, and the C++ OpenGL library. Using a combination of programming languages and their appropriate
libraries enabled me to explore the possibilities of multi-language and multi-library development.
I also undertook studies in the software development life cycle, where planning, development, testing, deployment, monitoring, and repeating revealed the
mechanics of a continuous integration and continuous development (CI/CD) pipeline. From planning using user stories, diagrams (use case, process, component,
data flow, sequence, activity, state machine, class, deployment, API, and call graph diagrams), pseudocode, business requirements documents (such as acceptance
criteria, technical specifications, system requirements, etc.), wireframes, and many more tools. Comparisons between different development styles were also
revealed, such as the Agile-Scrum methodology (utilizing short sprints for development) and the Waterfall methodology (which involves planning, coding, testing,
and deploying), providing insight into when each methodology is best implemented.
This project showcases artifacts from courses at SNHU's Software Engineering Program.
There are three enhancements on 2 artifacts. The first artifact is a Binary Search Tree that sorts a csv file of courses into
a search tree data structure. The first enhancement was to create more user functionality, offering an add custom course method
with a menu option, and a delete course method with a menu option.
These two additional functions run the risk of degrading the Binary Search Tree search time complexity from O(log n) to O(n). To prevent
this breakdown, enhancement two adds self-balancing algorithms into the insert and delete methods that will rotate the nodes of the tree should
it become unbalanced (See read me files for full explanations).
The last enhancement is done on artifact two, which is a graphical user interface (GUI) deployed on a webpage for filtering a database with animals.
The original artifact is scripted in Python using MongoDB and JSON formatted for database reads. The enhancement performed was converting from an online
database to an SQLite3 local database. This requires minimal setup for users to interact with. It provides a data table filtered by animal type and breed,
a data display pie chart, and an interactive geo-location map.
A lightweight inventory management web app built with vanilla HTML, CSS, and JavaScript.
A full stack web application built using MEAN (Mongo DB, Express, Angular, and Node.js). It provides a front-end user interface connected to a
backend administrator dashboard that allows CRUD operations for a trip destination website called Travler. Focus of the project was on backend development
(CRUD operations, authentication/authorization, and database exploration tools such as MongoDB Compass and Postman).
A project built to use Deep Q-Learning to train an agent to find a correct path through a 2 dimensional maze, using rewards and state based actions/decisions.
This project uses Python, Jupyter Notebook, Keras/TensorFlow, and reinforcement learning.
An Android inventory management app built in Java using SQLite. The app supports user authentication, user-specific inventory items, full CRUD operations, and SMS permission handling. Inventory items are displayed using RecyclerView and persisted locally
--Under Construction--
See TODO List
You can reach me at: AnthonyBaratti@gmail.com