Emerging Software Testing Technologies

Lonetti, Francesca; Marchetti, Eda

doi:10.1016/bs.adcom.2017.11.003

Cited by 18 publications

(10 citation statements)

References 94 publications

(164 reference statements)

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“…We therefore used performance tests (spike tests) and obtained quantitative values that could be used to measure the overall performance of the application and its interaction with end users. [16], [42], [59], [68], [69]. For this purpose, we used two AKS-controlled testing environments consisting of nine Docker instances (Ubuntu Server 18.04 LTS, 1 Core, 3 GB RAM, and no replicas) [14].…”

Section: Validation Of Resultsmentioning

confidence: 99%

Telemonitoring System for Infectious Disease Prediction in Elderly People Based on a Novel Microservice Architecture

et al. 2020

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This article describes the design, development and implementation of a set of microservices based on an architecture that enables detection and assisted clinical diagnosis within the field of infectious diseases of elderly patients, via a telemonitoring system. The proposed system is designed to continuously update a medical database fed with vital signs from biosensor kits applied by nurses to elderly people on a daily basis. The database is hosted in the cloud and is managed by a flexible microservices software architecture. The computational paradigms of the edge and the cloud were used in the implementation of a hybrid cloud architecture in order to support versatile high-performance applications under the microservices pattern for the pre-diagnosis of infectious diseases in elderly patients. The results of an analysis of the usability of the equipment, the performance of the architecture and the service concept show that the proposed e-health system is feasible and innovative. The system components are also selected to give a cost-effective implementation for people living in disadvantaged areas. The proposed e-health system is also suitable for distributed computing, big data and NoSQL structures, thus allowing the immediate application of machine learning and AI algorithms to discover knowledge patterns from the overall population.

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Section: Validation Of Resultsmentioning

confidence: 99%

Telemonitoring System for Infectious Disease Prediction in Elderly People Based on a Novel Microservice Architecture

et al. 2020

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“…The software architecture attempts to check its efficiency, integration, compatibility, and performance, counting errors when the components interact [54]. The testbed has two Docker containers (1 vCPU, 4 GB, 120 GB Disk, Ubuntu 16.04.6 LTS); Apache for the endpoint and Nginx as the frontend proxy and load balancer.…”

Section: System Efficiencymentioning

confidence: 99%

“…Nginx receives the user queries and forwards them to the microservices; Apache JMeter measures the workload [55]. BlazeMeter servers (US East-Virginia, AWS) simulate the workload [54,56]. Microservice #1 (MS1) provides a search of over 6297 records, and Microservice #2 (MS2) requests 138 records of residents with infectious diseases for 20 and 50 concurrent virtual users.…”

Section: System Efficiencymentioning

confidence: 99%

Medical Prognosis of Infectious Diseases in Nursing Homes by Applying Machine Learning on Clinical Data Collected in Cloud Microservices

Garcés-Jiménez

Calderón-Gómez

Pulido

et al. 2021

IJERPH

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Background: treating infectious diseases in elderly individuals is difficult; patient referral to emergency services often occurs, since the elderly tend to arrive at consultations with advanced, serious symptoms. Aim: it was hypothesized that anticipating an infectious disease diagnosis by a few days could significantly improve a patient’s well-being and reduce the burden on emergency health system services. Methods: vital signs from residents were taken daily and transferred to a database in the cloud. Classifiers were used to recognize patterns in the spatial domain process of the collected data. Doctors reported their diagnoses when any disease presented. A flexible microservice architecture provided access and functionality to the system. Results: combining two different domains, health and technology, is not easy, but the results are encouraging. The classifiers reported good results; the system has been well accepted by medical personnel and is proving to be cost-effective and a good solution to service disadvantaged areas. In this context, this research found the importance of certain clinical variables in the identification of infectious diseases. Conclusions: this work explores how to apply mobile communications, cloud services, and machine learning technology, in order to provide efficient tools for medical staff in nursing homes. The scalable architecture can be extended to big data applications that may extract valuable knowledge patterns for medical research.

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“…To evaluate the performance of the resources of each SPIDEP variant incorporating SOA and MSA (i.e., networks and infrastructure), spike testing was used to obtain quantitative values regarding the behavior of the services and their interaction with end users [53,89,105,106].…”

Section: Experiments Settingsmentioning

confidence: 99%

Evaluating Service-Oriented and Microservice Architecture Patterns to Deploy eHealth Applications in Cloud Computing Environment

et al. 2021

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This article proposes a new framework for a Cloud-based eHealth platform concept focused on Cloud computing environments, since current and emerging approaches using digital clinical history increasingly demonstrate their potential in maintaining the quality of the benefits in medical care services, especially in computer-assisted clinical diagnosis within the field of infectious diseases and due to the worsening of chronic pathologies. Our objective is to evaluate and contrast the performance of the architectural patterns most commonly used for developing eHealth applications (i.e., service-oriented architecture (SOA) and microservices architecture (MSA)), using as reference the quantitative values obtained from the various performance tests and their ability to adapt to the required software attribute (i.e., versatile high-performance). Therefore, it was necessary to modify our platform to fit two architectural variants. As a follow-up to this activity, corresponding tests were performed that showed that the MSA variant functions better in terms of performance and response time compared to the SOA variant; however, it consumed significantly more bandwidth than SOA, and scalability in SOA is generally not possible or requires significant effort to be achieved. We conclude that the implementation of SOA and MSA depends on the nature and needs of organizations (e.g., performance or interoperability).

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Emerging Software Testing Technologies

Cited by 18 publications

References 94 publications

Telemonitoring System for Infectious Disease Prediction in Elderly People Based on a Novel Microservice Architecture

Telemonitoring System for Infectious Disease Prediction in Elderly People Based on a Novel Microservice Architecture

Medical Prognosis of Infectious Diseases in Nursing Homes by Applying Machine Learning on Clinical Data Collected in Cloud Microservices

Evaluating Service-Oriented and Microservice Architecture Patterns to Deploy eHealth Applications in Cloud Computing Environment

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