Reliable Requirements Engineering Practices for COVID-19 Using Blockchain

Shahzad, Basit; Javed, Iqra; Shaikh, Asadullah; Sulaiman, Adel; Abro, Ahsanullah; Memon, Muhammad Ali

doi:10.3390/su13126748

Cited by 14 publications

(11 citation statements)

References 75 publications

(129 reference statements)

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“…Moreover, tools should target detected requirements errors, software process models, and functional project size. Researchers should also consider handling stakeholders' privacy [63], service level agreements that support measurable customer-oriented services, and knowledge representation and sharing [e.g., S02, S07, S13, S19, S25, S31, S32, S33, S36].…”

Section: ) Lack Of Tools and Datasetsmentioning

confidence: 99%

Challenges of Software Requirements Quality Assurance and Validation: A Systematic Literature Review

Atoum¹,

Baklizi

Alsmadi

et al. 2021

IEEE Access

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Section: ) Lack Of Tools and Datasetsmentioning

confidence: 99%

Challenges of Software Requirements Quality Assurance and Validation: A Systematic Literature Review

Atoum¹,

Baklizi

Alsmadi

et al. 2021

IEEE Access

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“…Liver disease is a common health issue. Therefore, early diagnosis of the risk factors will help medical physicians predict the development of the disease [ 27 ].…”

Section: Related Workmentioning

confidence: 99%

Prediction Model of Adverse Effects on Liver Functions of COVID-19 ICU Patients

Mashraqi

Halawani

Alelyani

et al. 2022

Journal of Healthcare Engineering

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SARS-CoV-2 is a recently discovered virus that poses an urgent threat to global health. The disease caused by this virus is termed COVID-19. Death tolls in different countries remain to rise, leading to continuous social distancing and lockdowns. Patients of different ages are susceptible to severe disease, in particular those who have been admitted to an ICU. Machine learning (ML) predictive models based on medical data patterns are an emerging topic in areas such as the prediction of liver diseases. Prediction models that combine several variables or features to estimate the risk of people being infected or experiencing a poor outcome from infection could assist medical staff in the treatment of patients, especially those that develop organ failure such as that of the liver. In this paper, we propose a model called the detecting model for liver damage (DMLD) that predicts the risk of liver damage in COVID-19 ICU patients. The DMLD model applies machine learning algorithms in order to assess the risk of liver failure based on patient data. To assess the DMLD model, collected data were preprocessed and used as input for several classifiers. SVM, decision tree (DT), Naïve Bayes (NB), KNN, and ANN classifiers were tested for performance. SVM and DT performed the best in terms of predicting illness severity based on laboratory testing.

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“…Shazad et al [67] conducted a systematic literature review to identify the challenges associated with building reliable COVID-19 software. The authors then proposed using blockchain to gather and negotiate the COVID-19 systems requirements.…”

Section: Restraining Covid-19mentioning

confidence: 99%

SPIN: A Blockchain-Based Framework for Sharing COVID-19 Pandemic Information across Nations

et al. 2021

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The COVID-19 pandemic has caused many countries around the globe to put strict policies and measures in place in an attempt to control the rapid spread of the virus. These measures have affected economic activities and have impacted a broad range of businesses, such as international traveling, restaurants, and shopping malls. As COVID-19 vaccination efforts progress, countries are starting to relax international travel constraints and permit passengers from certain destinations to cross the border. Moreover, travelers from those destinations are likely required to provide certificates of vaccination results or negative COVID-19 tests before crossing the borders. Implementing these travel guidelines requires sharing information between countries, such as the number of COVID-19 cases and vaccination certificates for travelers. In this paper, we introduce SPIN, a framework leveraging a permissioned blockchain for sharing COVID-19 information between countries. This includes public data, such as the number of vaccinated people, and private data, such as vaccination certificates for individuals. Additionally, we employ cancelable fingerprint templates to authenticate private information about travelers. We analyze the framework from scalability, efficiency, security, and privacy perspectives. To validate our framework, we provide a prototype implementation using the Hyperledger Fabric platform.

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Reliable Requirements Engineering Practices for COVID-19 Using Blockchain

Cited by 14 publications

References 75 publications

Challenges of Software Requirements Quality Assurance and Validation: A Systematic Literature Review

Challenges of Software Requirements Quality Assurance and Validation: A Systematic Literature Review

Prediction Model of Adverse Effects on Liver Functions of COVID-19 ICU Patients

SPIN: A Blockchain-Based Framework for Sharing COVID-19 Pandemic Information across Nations

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