Are These Requirements Risky: A Proposal of an IoT-Based Requirements Risk Estimation Framework

被引:1
|
作者
Gupta, Chetna [1 ]
Gupta, Varun [2 ]
机构
[1] Jaypee Inst Informat Technol, Dept Comp Sci & Engn, Noida 201305, India
[2] Univ Alcala, Dept Econ & Business Adm, Madrid 28802, Spain
关键词
Internet of Things; intuitionistic fuzzy logic; software engineering; requirements engineering; risk estimation; SOFTWARE; MANAGEMENT; INTERNET; THINGS;
D O I
10.3390/math10081210
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
Internet of Things (IoT) systems are revolutionizing traditional living to a new digital living style. In the past, a lot of investigations have been carried out to improve the technological challenges and issues of IoT and have focused on achieving the full potential of IoT. The foremost requisite for IoT software system developers seeking a competitive edge is to include project-specific features and meet customer expectations effectively and accurately. Any failures during the Requirements Engineering (RE) phase can result in direct or indirect consequences for each succeeding phase of development. The challenge is far more immense because of the lack of approaches for IoT-based RE. The objective of this paper is to propose a requirements risk management model for IoT systems. The method regarding the proposed model estimates requirements risk by considering both customers' and developers' perceptions. It uses multiple criteria using intuitionistic fuzzy logic and analytical technique. This will help to handle the uncertainty and vagueness of human perception, providing a well-defined two-dimensional indication of customer value and risk. The validity of the approach is tested on real project data and is supported with a user study. To the best of our understanding, literature lacks the trade-off analysis at the RE level in IoT systems and this presented work fills this prerequisite in a novel way by improving (i) requirements risk assessment for IoT systems and (ii) handling developers' subjective judgments of multiple conflicting criteria, yielding more concrete and more observable results.
引用
收藏
页数:13
相关论文
共 50 条
  • [31] An Orchestrator Framework for IoT-based Disaster Prevention Simulation
    Hiroi, Kei
    Kohiga, Akihito
    Fukaya, Sho
    Shinoda, Yoichi
    2023 IEEE SENSORS, 2023,
  • [32] A Framework for IoT-Based Monitoring and Diagnosis of Manufacturing Systems
    Yen, I-Ling
    Zhang, Shuai
    Bastani, Farokh
    Zhang, Yuqun
    2017 11TH IEEE SYMPOSIUM ON SERVICE-ORIENTED SYSTEM ENGINEERING (SOSE), 2017, : 1 - 8
  • [33] A Reputation Framework to Share Resources into IoT-based Environments
    De Meo, Pasquale
    Messina, Fabrizio
    Postorino, Maria Nadia
    Rosaci, Domenico
    Sarne, Giuseppe M. L.
    PROCEEDINGS OF THE 2017 IEEE 14TH INTERNATIONAL CONFERENCE ON NETWORKING, SENSING AND CONTROL (ICNSC 2017), 2017, : 513 - 518
  • [34] An IoT-based Framework to Protect Cultural Heritage Buildings
    Colace, Francesco
    Elia, Cristina
    Guida, Caterina Gabriella
    Lorusso, Angelo
    Marongiu, Francesco
    Santaniello, Domenico
    2021 IEEE INTERNATIONAL CONFERENCE ON SMART COMPUTING (SMARTCOMP 2021), 2021, : 377 - 382
  • [35] Requirements Risk Estimation using TOPSIS Method
    Gupta, Chetna
    Gupta, Varun
    2020 27TH ASIA-PACIFIC SOFTWARE ENGINEERING CONFERENCE (APSEC 2020), 2020, : 505 - 506
  • [36] Requirements, desired characteristics and architectural proposal for a visualization framework for digital pathology
    Kimpe, Tom
    Avanaki, Ali
    Espig, Kathryn
    Rostang, Johan
    Marchessoux, Cedric
    Piepers, Bastian
    Xthona, Albert
    MEDICAL IMAGING 2014: DIGITAL PATHOLOGY, 2014, 9041
  • [37] Categorisation of Requirements in the Ontology-Based Framework for Employer Information Requirements (OntEIR)
    Dwairi, Shadan
    Mahdjoubi, Lamine
    BUILDINGS, 2022, 12 (11)
  • [38] Flood risk mapping for the lower Narmada basin in India: a machine learning and IoT-based framework
    Mangukiya, Nikunj K.
    Sharma, Ashutosh
    NATURAL HAZARDS, 2022, 113 (02) : 1285 - 1304
  • [39] Flood risk mapping for the lower Narmada basin in India: a machine learning and IoT-based framework
    Nikunj K. Mangukiya
    Ashutosh Sharma
    Natural Hazards, 2022, 113 : 1285 - 1304
  • [40] Precept-Based Framework for Using Crowdsourcing in IoT-based Systems
    Vora, Urjaswala
    Chomal, Peeyush
    Vakharwala, Avani
    2019 IEEE INTERNATIONAL CONFERENCE ON SMART COMPUTING (SMARTCOMP 2019), 2019, : 387 - 392