| Pub. Date | : Sep, 2022 |
|---|---|
| Product Name | : The IUP Journal of Information Technology |
| Product Type | : Article |
| Product Code | : IJIT010922 |
| Author Name | : Kuhaneswaran Banujan and Nirubikaa Ravikumar |
| Availability | : YES |
| Subject/Domain | : Engineering |
| Download Format | : PDF Format |
| No. of Pages | : 20 |
Agile Software Development (ASD) is an iterative method of project management and software development that enables teams to provide customer value more quickly with fewer complications. Product Backlog Items (PBI) are a prioritized list to-be-implemented ASD requirements. Prior to beginning sprinting in the ASD, one of the most crucial duties is the classification of PBI. Using Machine Learning and Deep Learning methods, the authors sought to categorize the PBI into Spikes, Foundational stories and User stories. They initially gathered data from numerous software development initiatives and web sources. Each PBI was classified manually as Spikes, Foundational stories, or User stories and preprocessed to remove superfluous text content. Using the TF-IDF and GloVe techniques, the preprocessed PBI were then embedded with words. ANN and LSTM were used to classify the PBIs. The paper models combinations of TF-IDF+ANN, GloVe+ANN and GloVe+LSTM. With an accuracy of 92.4%, the GloVe+LSTM model surpassed other deployed models.
The use of standard business procedures in the development of software applications is known as the Software Development Life Cycle (SDLC) (Leau et al., 2012; and Mishra and Dubey, 2013). The main objective of SDLC is to produce the finest software in the shortest amount of time, while meeting customer expectations. The traditional waterfall model is more rigid (Alshamrani and Bahattab, 2015; and Petersen et al., 2009) and is entirely based on adhering to a set of instructions that keeps the group moving forward. In this form, there is no space for last-minute adjustments or amendments. Rework will be required if the project's requirements alter suddenly.
Agile Software Development (ASD), Product Backlog Items (PBI), Spikes, Foundational stories, User stories, Deep Learning (DL), Long Short-Term Memory (LSTM), Artificial Neural Networks (ANN) and GloVe