Towards a New Framework of Software Reliability Measurement Based on Software Metrics

Amara, Dalila; Rabai, Latifa Ben Arfa

doi:10.1016/j.procs.2017.05.428

Cited by 15 publications

(5 citation statements)

References 15 publications

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“…Another important point of the research is that the values calculated for each metric show differences from one tool to another, which may occur due to the size of the software. Amara and Rabai (2017) conducted a review of the methods used to measure software reliability and proposed a new approach for this measurement based on software metrics that can be used at each stage of the software development lifecycle (SDLC), therefore producing reliable software instead of evaluating the reliability of the finished product. In the proposed approach, the use of reliability models and techniques starts in the Requirements Elicitation phase, aiming to improve reliability, developing the necessary specifications, and avoiding unnecessary tests.…”

Section: Software Metrics Studiesmentioning

confidence: 99%

Literature review on software metrics and a New Proposal

Barcelos

Gomes

Sanseverino

et al. 2021

POEE

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The use of metrics is important in software development activities as they make it possible to check quality, identify failures and other benefits. The objective of this paper is to propose a new software metric based on a bibliometric study and a literature review on software metrics. The bibliometric research was carried out in the Scopus and Web of Science databases to identify the distribution of articles by year of publication, the main authors, affiliation, country, the most common languages, the types of documents, journals with more publications, areas of knowledge, and the keyword clusters. Twenty-three articles were subsequently selected for reading to compose the literature review. The results of the bibliometric research show that (i) there is no defined core of research; (ii) there is a fluctuation of the number of published articles; (iii) the predominant language is English, and the country with the highest index of publications is the United States; (iv) the main area of knowledge is computer science; (v) in relation to affiliation, Florida Atlantic University stands out; (vi) the journal with the largest number of publications is the Journal of Systems and Software. The literature review showed that many software metrics can be used for different purposes, but most of them are related to code, and none are related to acceptance. As such, a support metric for the software acceptance process is proposed to facilitate the delivery phase of the software product, providing security for the customer and cost savings for the developing company.

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Section: Software Metrics Studiesmentioning

confidence: 99%

Literature review on software metrics and a New Proposal

Barcelos

Gomes

Sanseverino

et al. 2021

POEE

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show abstract

“…Software quality is described through a number of attributes and aims to identify their capability to achieve the software requirements [19]. In addition, Crosby defines software quality as meeting client requirements with zero error.…”

Section: The Concept Of Software Qualitymentioning

confidence: 99%

Determining the Tested Classes with Software Metrics

Yücalar¹,

Borandağ²

2017

Celal Bayar Üniversitesi Fen Bilimleri Dergisi

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Early detection and correction of errors appearing in software projects reduces the risk of exceeding the estimated time and cost. An efficient and effective test plan should be implemented to detect potential errors as early as possible. In the earlier phases, codes can be analyzed by efficiently employing software metric and insight can be gained about error susceptibility and measures can be taken if necessary. It is possible to classify software metric according to the time of collecting data, information used in the measurement, type and interval of the data generated. Considering software metric depending on the type and interval of the data generated, object-oriented software metric is widely used in the literature. There are three main metric sets used for software projects that are developed as object-oriented. These are Chidamber & Kemerer, MOOD and QMOOD metric sets. In this study, an approach for identifying the classes that should primarily be tested has been developed by using the objectoriented software metric. Then, this approach is applied for selected versions of the project developed. According to the results obtained, the correct determination rate of sum of the metrics method, which was developed to identify the classes that should primarily be tested, is ranged between 55% and 68%. In the random selection method, which was used to make comparisons, the correct determination rate for identifying the classes that should primarily be tested is ranged between 9.23% and 11.05%. In the results obtained using sum of the metrics method, a significant rate of improvement is observed compared to the random selection method.

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“…Maximum Likelihood Assessment (MLE) is a common statistical method for the determination of the probability distribution parameters underlying a given dataset. Throughout the literature, there are many predictive models of the reliability of software-based neural networks, which are better known than certain statistical models [4][5][6]. Computer reliability is one of the key factors taken into account in maintaining the accuracy of the computer.…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Quartile Deviation-based Support Vector Regression Model for Software Reliability Datasets

Reddy¹,

Prasanth²

2022

IJACSA

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Software reliability estimation using machine learning play a major role on the different software quality reliability databases. Most of the conventional software reliability estimation model fails to predict the test samples due to high true positive rate of the traditional support vector regression models. Most of the traditional machine learning based fault prediction models are integrated with standard software reliability growth measures for reliability severity classification. However, these models are used to predict the reliability level of binary class with less standard error. In this paper, a hybrid support vector regression-based quartile deviation growth measure is implemented on the training fault datasets. Experimental results are simulated on various reliability datasets with different configuration parameters for fault prediction.

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Towards a New Framework of Software Reliability Measurement Based on Software Metrics

Cited by 15 publications

References 15 publications

Literature review on software metrics and a New Proposal

Literature review on software metrics and a New Proposal

Determining the Tested Classes with Software Metrics

A Hybrid Quartile Deviation-based Support Vector Regression Model for Software Reliability Datasets

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