An Optimization Model for Software Quality Prediction With Case Study Analysis Using MATLAB

Gheisari, Mehdi; Panwar, Deepak; Tomar, Pradeep; Harsh, Harshwardhan; Zhang, Xiaobo; Solanki, Arun; Nayyar, Anand; Alzubi, Jafar A.

doi:10.1109/access.2019.2920879

Cited by 44 publications

(19 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Mehdi Gheisari et al [82] developed a mathematical model for optimal prediction of stakeholder satisfaction. The model used constraint equations and validated real data using the impact of relationships among different quality parameters.…”

Section: Loh and Leementioning

confidence: 99%

Analysis and Assessment of Existing Software Quality Models to Predict the Reliability of Component-Based Software

Yadav¹

2020

IJETER

View full text Add to dashboard Cite

Software engineering is an approach pre-owned by the researchers and innovators to reduce the ratio of crisis in software. Therefore the designer/ innovator can readily design a valuable quality software, by using various approaches like Component-Based Software Engineering (CBSE). The components quality has a high impact on the quality of a whole application. Several quality models for CBSE and Component-Off-The-Shelf (COTS) are available in the literature so this paper presents various quality models with defined parameters for quality prediction. Several models, like, Boehm's, McCall's, FURPS, ISO 9126, Dromey's, have been developed for quality evaluation using hierarchically related characteristics of quality indicators. Over the years, some models have been developed for structuring software quality for software. Nowadays, researchers are showing their passion for innovation in the area of software reliability. The reliability of a software component relies on the following factors like the reliability of services, environment frequency so finally this paper presents the analysis and assessment of software quality models and their quality parameters for CBS by going through various researchers and practitioners' work.

show abstract

Section: Loh and Leementioning

confidence: 99%

Analysis and Assessment of Existing Software Quality Models to Predict the Reliability of Component-Based Software

Yadav¹

2020

IJETER

View full text Add to dashboard Cite

show abstract

“…Nayyar et al [51][52][53][54][55][56][57] have provided a detailed understanding on evolutionary algorithms including GA, and swarm based algorithms including ACO, ABO, PSO, Glow worm, Cockroach swarm optimization, Cat swarm optimization, Dolphin echo location, Eagle strategy, monkey search algorithm etc., highlighting the various computational models, the versatile approaches along with their applications in the newly emerging complex fields of engineering including IOT, AI, Big data, Data mining and Robotics. Panda et al [23] have provided a detailed overview of the popular metaheuristic algorithms since last two decades including Cuckoo Search(CS), Gravitational search algorithm(GSA), Genetic Algorithms(GA), Particle swarm optimization(PSO), Differential Evolution(DE) and Artificial Bee Colony algorithm(ABC) and have compared the performances of the algorithms to generate test data for path coverage based testing.…”

Section: Literature Reviewmentioning

confidence: 99%

Test Suit Generation for Object Oriented Programs: A Hybrid Firefly and Differential Evolution Approach

et al. 2020

Self Cite

View full text Add to dashboard Cite

In model-based testing, the test suites are derived from design models of system specification documents instead of actual program codes to reduce cost and time of testing. In search-based software testing approach, the nature inspired meta-heuristic search algorithms are used for automating and optimizing the test suite generation process of software testing. This paper proposes a concrete model-based testing framework; using UML behavioral state chart model along with the hybrid version of the two most popular nature inspired algorithms, Firefly algorithm (FA) and Differential Algorithm (DE). The hybrid algorithm is adopted to generate optimized test suits for the benchmark triangle classification problem. Experimental results evidently show that the hybrid FADE search algorithm outperforms the individual model-based Firefly and Differential Evolution algorithm's performances in terms of time complexity, better exploration and exploitation as well as variations in test case generation process. The framework generates optimized test data for complete transition path coverage of the available feasible paths of the example problem.

show abstract

“…They used machine learning for malicious traffic detection. In detail, they used Support Vector Machine (SVM) for classifying data and detecting abnormal hosts conditions [19]. They also tried to select features of current attack.…”

Section: Related Workmentioning

confidence: 99%

ECA: An Edge Computing Architecture for Privacy-Preserving in IoT-Based Smart City

et al. 2019

Self Cite

View full text Add to dashboard Cite

Recently, IoT has greatly influenced our daily lives through various applications. One of the most promising application is smart city that leverages IoT devices to manage cities without any human intervention. The high possibility of sensing and publishing sensitive data in this smart environment leads to three significant issues: (1) privacy-preserving (2) heterogeneity, and (3) real-time services. We observe that current studies are in lack of addressing these challenges. In this paper, we propose a new privacy-preserving architecture for IoT devices in the smart city by leveraging ontology, a data model, at the edge of the network. At first, we propose an ontology that consists of privacy information of devices. Then, we mount a real-time privacy-preserving method on top of it that is achieved by providing a dynamic environment from the privacy-preserving point of view. Based on the simulation results using Protege and Visual Studio on a synthetic dataset, we find that our solution provides privacy at real-time while addressing heterogeneity issue so that many IoT devices can afford it. Thus, our proposed solution can be widely used for smart cities.

show abstract

An Optimization Model for Software Quality Prediction With Case Study Analysis Using MATLAB

Cited by 44 publications

References 14 publications

Analysis and Assessment of Existing Software Quality Models to Predict the Reliability of Component-Based Software

Analysis and Assessment of Existing Software Quality Models to Predict the Reliability of Component-Based Software

Test Suit Generation for Object Oriented Programs: A Hybrid Firefly and Differential Evolution Approach

ECA: An Edge Computing Architecture for Privacy-Preserving in IoT-Based Smart City

Contact Info

Product

Resources

About