Requirements Engineering Practices and Challenges in the Context of Big Data Software Development Projects: Early Insights from a Case Study
Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
Standard
Requirements Engineering Practices and Challenges in the Context of Big Data Software Development Projects : Early Insights from a Case Study. / Arruda, Darlan; Laigner, Rodrigo.
Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020. ed. / Xintao Wu; Chris Jermaine; Li Xiong; Xiaohua Tony Hu; Olivera Kotevska; Siyuan Lu; Weijia Xu; Srinivas Aluru; Chengxiang Zhai; Eyhab Al-Masri; Zhiyuan Chen; Jeff Saltz. IEEE, 2020. p. 2012-2019 9377734.Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
Harvard
APA
Vancouver
Author
Bibtex
}
RIS
TY - GEN
T1 - Requirements Engineering Practices and Challenges in the Context of Big Data Software Development Projects
T2 - 8th IEEE International Conference on Big Data, Big Data 2020
AU - Arruda, Darlan
AU - Laigner, Rodrigo
PY - 2020
Y1 - 2020
N2 - This paper reports on the results of an exploratory case study on a large-scale Big Data systems development project in the OilGas domain within a non-profit organisation. The aim of this study was to investigate the RE practices and challenges in such projects, currently bereft in the scientific literature. This investigation was focused on: (a) RE practices; (b) sources and distribution of requirements; (c) the role of Big Data characteristics and technologies in RE and systems design; and (d) RE challenges in engineering Big Data Systems. The main results show that (a) there is a lack of specific project tailored RE practices, tools, and frameworks for elicitation, specification and modelling, analysis, and prioritisation of requirements; (b) 40% of the system's requirements are considered Big Data-related from which 75% are identified from internal sources; (c) Big Data characteristics and technologies play an important role in defining quality requirements and system's architecture; (d) five challenges in eliciting, documenting, and analysing Big Data related requirements were identified and discussed. The findings suggest academics and practitioners opportunities to engage in further research in this area.
AB - This paper reports on the results of an exploratory case study on a large-scale Big Data systems development project in the OilGas domain within a non-profit organisation. The aim of this study was to investigate the RE practices and challenges in such projects, currently bereft in the scientific literature. This investigation was focused on: (a) RE practices; (b) sources and distribution of requirements; (c) the role of Big Data characteristics and technologies in RE and systems design; and (d) RE challenges in engineering Big Data Systems. The main results show that (a) there is a lack of specific project tailored RE practices, tools, and frameworks for elicitation, specification and modelling, analysis, and prioritisation of requirements; (b) 40% of the system's requirements are considered Big Data-related from which 75% are identified from internal sources; (c) Big Data characteristics and technologies play an important role in defining quality requirements and system's architecture; (d) five challenges in eliciting, documenting, and analysing Big Data related requirements were identified and discussed. The findings suggest academics and practitioners opportunities to engage in further research in this area.
KW - Big Data Challenges
KW - Big Data Requirements
KW - Big Data Systems
KW - Case Study
KW - Requirements Engineering
UR - http://www.scopus.com/inward/record.url?scp=85103852039&partnerID=8YFLogxK
U2 - 10.1109/BigData50022.2020.9377734
DO - 10.1109/BigData50022.2020.9377734
M3 - Article in proceedings
AN - SCOPUS:85103852039
SP - 2012
EP - 2019
BT - Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020
A2 - Wu, Xintao
A2 - Jermaine, Chris
A2 - Xiong, Li
A2 - Hu, Xiaohua Tony
A2 - Kotevska, Olivera
A2 - Lu, Siyuan
A2 - Xu, Weijia
A2 - Aluru, Srinivas
A2 - Zhai, Chengxiang
A2 - Al-Masri, Eyhab
A2 - Chen, Zhiyuan
A2 - Saltz, Jeff
PB - IEEE
Y2 - 10 December 2020 through 13 December 2020
ER -
ID: 260406923