A Neural Blockchain for Requirements Traceability: BC4RT Prototype

2Citations
Citations of this article
4Readers
Mendeley users who have this article in their library.
Get full text

Abstract

The ever-increasing globalization of the software industry presents challenges related to requirements engineering activities. Managing requirements’ changes and tracing software artifacts is not trivial in a multi-site environment composed of a variety of stakeholders that do not trust each other. In this study, we propose a neural blockchain prototype for the traceability of requirements (BC4RT) throughout the software development lifecycle in interorganizational software projects. The prototype is implemented using a neural blockchain platform, namely NDL ArcaNet, due to its inherent properties: performance efficiency, sustainability, and scalability. Besides these features, the proposed prototype provides a holistic and reliable view of software artifacts, requirements’ changes, and trace links. The increased visibility enhances collaboration, communication, and trust among stakeholders, and can potentially improve software development efficiency and quality.

Cite

CITATION STYLE

APA

Demi, S., Colomo-Palacios, R., Sánchez-Gordón, M., Velasco, C., & Cano, R. (2022). A Neural Blockchain for Requirements Traceability: BC4RT Prototype. In Communications in Computer and Information Science (Vol. 1646 CCIS, pp. 45–59). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-15559-8_4

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free