Grickit Movie Decision Project
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This project focused on Grickit, the Movie Decision Making tool created by William Vuong and Michael Long with the guidance of Dr. Steven D. Sheetz, the client. The final report has three main sections: the user’s manual, the developer’s manual, and our lessons learned. The user’s manual is a guide for a person who intends to utilize the Movie Grickit that was created, and wants more information about the Grickit and its purpose. Included is a general overview as well as an in depth look at the roles available for users of the Grickit system. We explore how each user affects the Grickit system to ultimately calculate and display the intended results. Included are screenshots so that the reader can easily identify the features referenced in the report. The developer’s manual is a guide for future developers to understand our design choices and the structure of our Grickit implementation. It begins with a high level overview of the technical workflow. Then is information about the RESTful web API created to store the Grickits and handle calculations. We discuss the various technology choices utilized in creating this API. The accompanying live documentation is discussed and shown to the developer through example use cases. Validation of user entered data and regression testing were done to ensure a good user experience. The developer’s manual also contains information about the front-end implementation. This section starts with the general design and thought process for creating the Movie Grickit. We describe technologies chosen and how they were utilized. Examples are shown with code snippets, about how the technology is used in the scope of this project. Interesting considerations taken with the creation of the front end have been noted and discussed. Included throughout the developer’s manual are screenshots to give a visual representation of the design choices. The lessons learned section contains the issues addressed while developing this tool, and our solutions. The main issues arose when deploying on the server identified by our client. The hardware was older (Windows Server 2003) and therefore we had versioning issues with the technologies we were using and the minimum OS supported. Our database solution required a newer OS, so we pivoted to a different storage solution, that utilizes a similar noSQL structure where data is stored in a file. This is not the optimal solution but was appropriate given the circumstances. We also had issues with the website needing to be retrieved through HTTPS. Therefore any calls using HTTP were routed through our HTTPS server. Our choice in separation of responsibilities for the AHP algorithm and our presentation layer were due to the goal of later producing a generalized Grickit that does not depend on a specific domain set. Our back-end solution has no notion of the movie data in our Movie Grickit. We suggest that modifications are made on top of our solution instead of starting from scratch when expanding, as our back-end will be a good base for when a generalized front-end is created. The Movie Grickit was an interesting project that had many considerations to take note of in both the back-end handling of the AHP algorithm and data storage, as well as the front-end user experience and design choices. Considerations were kept in mind for the future generalized solution with the back-end already ready to support a generalized solution. We were able to deploy on the intended hardware despite some minor obstacles. Overall the client was happy with the end result and will be moving forward with the project to expand its use cases.