Retro: Technical Report

Carroll, Ben (2021) Retro: Technical Report. Undergraduate thesis, Dublin, National College of Ireland.

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Abstract

A large number of modern Software Development teams have team members in different locations, and this factor has of course increased with many people working remotely due to the pandemic (Taplin, 2021). As most Software Development teams follow an Agile sprint methodology, remote working affect s their ability to carry out retrospectives, which are typically done in person. An Agile sprint is a short, time-bound period where teams complete a defined amount of work and a retrospective is carried out after a sprint in order to discuss how it went with regards to individuals, interactions, processes, tools (Scrum, 2021). Similarly, it has become increasingly difficult for Software Development team managers to effectively manage and gauge team moral when working remotely.

This report details the background, requirements gathering, design and implementation of Retro, an implementation of a solution to this problem. Retro is a web application that allows Software Development teams to be able to facilitate their agile sprint retrospectives remotely and enables managers of Software Development teams to effectively manage remotely through a Sentiment Analysis (mining of text that finds and extracts information that helps a person understand the sentiment behind the data [Gupta, 2018]) that is performed on a retrospective, allowing managers to gauge team morale, with the data to back the analysis up.

Retro’s implemented solution offers a lightweight, speedy web application that can be used by any Software Development team or enterprise to perform retrospectives. Its minimalist and user-friendly user interface places focus on the retrospectives and allows teams to address issues that have arisen from their retrospectives in real-time without compromising on functionality is also an advantage. Similarly, it allows Software Development team managers to effectively gauge team morale through its Sentiment Analysis functionality.

Item Type:	Thesis (Undergraduate)
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science Q Science > QA Mathematics > Computer software T Technology > T Technology (General) > Information Technology > Computer software Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4150 Computer Network Resources > The Internet > World Wide Web > Websites > Website Design T Technology > TK Electrical engineering. Electronics. Nuclear engineering > Telecommunications > The Internet > World Wide Web > Websites > Website Design Q Science > QA Mathematics > Computer software > Website Design T Technology > T Technology (General) > Information Technology > Computer software > Website Design
Divisions:	School of Computing > Bachelor of Science (Honours) in Computing
Depositing User:	Clara Chan
Date Deposited:	19 Aug 2021 13:45
Last Modified:	16 Sep 2021 16:04
URI:	https://norma.ncirl.ie/id/eprint/4983

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