MODEL-Based Performance Quality Assessment for IoT Applications

Dublin Core

Title

MODEL-Based Performance Quality Assessment for IoT Applications

Subject

internet of things
IoT
prediction
MBT
quality assurance
performance prediction.

Description

The number of applications incorporating Internet of Things (IoT) concepts increases extraordinarily. This increase cannot continue without high-quality assurance. There are some difficulties in testing IoT applications; the system heterogeneity, test cost and time are taken to test the system, and the precision percentage of test results.A well-known and possibly the best solution to overcoming these difficulties is to model the system for evaluation purposes, known as model-based testing (MBT). This paper aims to design a model-based testing approach to assess IoT applications performance quality attributes. The ISO 25000 quality model is used as a standard for software quality assurance applications. IoTMaaS is used as a case study to implement the methodological approach. The possible test cases were generated using the ACTS combinatorial test generation tool. The performance metrics of each test case were monitored until the optimum test case was identified, with the shortest response time and the least amount of resources used. The proposed testing method appears to be successful, according to the results.

Creator

Kh., Teeba Ismail
Hamarash, Ibrahim I.

Source

International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 12 (2021); pp. 4-20
1865-7923

Publisher

International Association of Online Engineering (IAOE), Vienna, Austria

Date

2021-06-18

Rights

Copyright (c) 2021 Teeba Ismail Kh., Ibrahim I. Hamarash

Relation

Format

application/pdf

Language

eng

Type

info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article

Identifier

Citation

Kh., Teeba Ismail and Ibrahim Hamarash I., MODEL-Based Performance Quality Assessment for IoT Applications, International Association of Online Engineering (IAOE), Vienna, Austria, 2021, accessed September 25, 2024, https://igi.indrastra.com/items/show/1964

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