Final Report - Lessons Learned (3-5 pages)

-[individual] what you learned in this project; for example: how had the project helped improve your understanding of CS-related principles, concepts or theories?

I learned a lot in this project; from working as a team and using new and different sources to new computer science related principles and tools. Coding as a team was new to me and always seemed like a challenge when thinking about it in the past. GitHub was great for that purpose because it allowed us to create a repository of what parts needed to be accomplished and different team members could work on those parts while not affecting other group members' progress on other parts of the project. Natural language processing was a new concept to me and it really expanded my learning experience because of how it combines computer science and artificial intelligence with the English language. I had no idea about tools like NLTK and how powerful of a tool that is with natural language processing. I used my experience from Software Engineering and function points to logically think about how processing language could actually help to analyze and predict the weights of function points automatically.

-how had your CS background helped with this project?

I consider myself a decent code writer, but no expert in one particular language so that may have helped me adapt to Python. Python reminded me a lot of Perl, which I had taken a course in previously so that also helped me get on the path to learning Python. Also, the document creation part was not new to me because of all the exhaustive documents I had created in Software Engineering, Technical Writing, and Policies and Procedures classes. It also seems like there is a group project in about every CS class, so working as a team was not new to me. I do enjoy the English language and learning about all the ways to manipulate words and sentences was rather fun as opposed to being a chore.

-[individual or team] if you had the chance to do it over, what would you do differently

If I had the chance to do this project over, there wouldn't be much I would change. An unfortunate part of this project was all the preliminary research we had to do before we actually started the project. We spent maybe a month researching the tools we needed to actually to start/complete the project and that set us back a little bit as far as being able to complete the stretch goal. The stretch goal would've been very interesting to complete as far as being able to automatically assign weights to function points. Although I believe what we accomplished with all the language processing and the statistics we were able to gather was still something to be proud of.

-[team] based on your experience, suggest some future extensions

An extension for this project would be to follow up with the client's goals and see about the automation of function points through natural language processing. That's a really intriguing concept, especially since my Software Engineering professor had in a PowerPoint slide that it is impossible to automate the estimation of function points. There seem to be a few companies out there that actually do this probably in a similar fashion to how we were going to approach it.

An extension to the class would maybe have there be a room somewhere in the building that teams could reserve for meetings or online meetings to be able to guarantee a private meeting area instead of taking chances that a small room near the Atrium will open up. I often see many vacant rooms in the building in the evenings and it would be great to give Capstone students access to just one of those by allowing them to reserve times through the professor or something similar.

rennX / FunctionPointParser

Final Report - Lessons Learned (3-5 pages) #32