Banca de QUALIFICAÇÃO: JOELDSON COSTA DAMASCENO

Uma banca de QUALIFICAÇÃO de MESTRADO foi cadastrada pelo programa.
STUDENT : JOELDSON COSTA DAMASCENO
DATE: 15/12/2023
TIME: 14:00
LOCAL: https://meet.google.com/sth-gbst-vop
TITLE:

REQUIREMENTS ENGINEERING AIDED BY SMART CHATBOTS: AN ASSESSMENT OF THE QUALITY OF ARTIFACTS

KEY WORDS:

Requirements Engineering; Generative Artificial Intelligence; Smart Chatbot; Requirements Artifacts.

PAGES: 150
BIG AREA: Ciências Exatas e da Terra
AREA: Ciência da Computação
SUMMARY:

Requirements Engineering is an essential process of collecting, documenting, and maintaining software requirements aligned with business objectives. The requirements elicitation phase is the starting point of software development, and it is a crucial, complex and time-consuming activity. To perform this role, requirements professionals need several skills, such as effective communication, analytical thinking, empathy, conflict resolution skills, moderation, self-confidence, and persuasion. Unfortunately, the significant shortage of specialized professionals has negatively impacted production, especially the quality of deliveries. Statistics reveal a considerable amount of failures in software products due to problems in the requirements engineering stage. However, recent research points to the promising use of generative artificial intelligence as a solution to improve requirements engineering. Artificial intelligence tools have the potential to automate tasks such as requirements gathering and analysis, as well as to assist in identifying and correcting ambiguous or incomplete requirements. In this study, our goal is to evaluate the quality of requirements artifacts generated with the help of intelligent chatbots. To do so, we are going to establish a group of professionals working in requirements engineering, providing them with a common requirement and requesting the elaboration of a set of artifacts. Then, we applied a data collection questionnaire containing specific questions to get the participants' impressions about the use of the tool during the process. Based on these inputs, we will analyze several aspects to measure the quality of the artifacts generated using quality metrics widely recognized in the market. We hope that this research contributes to the advance and efficiency of requirements engineering with the aid of artificial intelligence, improving the quality and success of software development projects.

COMMITTEE MEMBERS:
Presidente - 2978747 - CHARLES ANDRYE GALVAO MADEIRA
Externo ao Programa - 1671962 - EDUARDO HENRIQUE DA SILVA ARANHA - UFRNExterna ao Programa - 2245086 - ISABEL DILLMANN NUNES - UFRN