Early Test Effort Prediction using UML Diagrams

Sahoo, Pulak; Mohanty, Jnyana Ranjan

doi:10.11591/ijeecs.v5.i1.pp220-228

Cited by 15 publications

(11 citation statements)

References 6 publications

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“…In aspect-oriented programming paradigm, software development and testing are different from other programming paradigms as it supports the concept of Separation of Concerns (SoC) [7], [8]. As observed in Table 4, only a few approaches have used the UML behavior models for testing Aspect-Oriented Programs.…”

Section: Support Of Uml Behavior Model For Aspect-oriented Testing Apmentioning

confidence: 99%

“…Efficient and effective test model can be designed by directly using the UML behavioral models. Designing specific test model for testing is a tedious and time-consuming task [8]. Usage of UML behavioral model to test AOP reduces the effort and increases reusability.…”

Section: Support Of Uml Behavior Model For Aspect-oriented Testing Apmentioning

confidence: 99%

“…But in case of testing aspect-oriented programs, all coverage criteria related to traditional programming paradigms cannot be used directly as there is a concept of SoC [3]. Therefore, need to extend the coverage criteria for testing AOP [8]. Study of literature indicates that only three testing coverage criteria are defined [3].…”

Section: Test Case Coverage Criteriamentioning

confidence: 99%

See 2 more Smart Citations

Comparative Analysis of Various Testing Techniques used for Aspect-Oriented Software System

Dalal¹,

Hooda²

2018

IJEECS

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<p>Nowadays, Aspect-Oriented Programming (AOP) paradigm is getting more popularity in the field of software development. But testing an Aspect-oriented software system (AOSS) is not well matured. Therefore, many researchers have been focusing on testing an AOSS. Moreover, the literature indicates that very few papers have devoted to literature survey but still there is need to study in depth of various testing techniques used for AOSS. Therefore, in this paper, a comprehensive study of existing various testing techniques for AOSS have been conducted and present a comparative analysis result of various testing techniques based on various parameters.</p>

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Section: Support Of Uml Behavior Model For Aspect-oriented Testing Apmentioning

confidence: 99%

Section: Support Of Uml Behavior Model For Aspect-oriented Testing Apmentioning

confidence: 99%

Section: Test Case Coverage Criteriamentioning

confidence: 99%

See 1 more Smart Citation

Comparative Analysis of Various Testing Techniques used for Aspect-Oriented Software System

Dalal¹,

Hooda²

2018

IJEECS

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“…Data mining ors software analytics studies that use requirements engineering artifacts are scarce [9]. For example, one of these rare studies aims early test effort prediction by using UML diagrams [10]. On the other hand, software data mining studies which are based on sofware code and code change artifacts are common [9].…”

Section: Introductionmentioning

confidence: 99%

Using Data Mining to Identify COSMIC Function Point Measurement Competence

Bağrıyanık

Karahoca

2018

IJECE

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Cosmic Function Point (CFP) measurement errors leads budget, schedule and quality problems in software projects. Therefore, it’s important to identify and plan requirements engineers’ CFP training need quickly and correctly. The purpose of this paper is to identify software requirements engineers’ COSMIC Function Point measurement competence development need by using machine learning algorithms and requirements artifacts created by engineers. Used artifacts have been provided by a large service and technology company ecosystem in Telco. First, feature set has been extracted from the requirements model at hand. To do the data preparation for educational data mining, requirements and COSMIC Function Point (CFP) audit documents have been converted into CFP data set based on the designed feature set. This data set has been used to train and test the machine learning models by designing two different experiment settings to reach statistically significant results. Ten different machine learning algorithms have been used. Finally, algorithm performances have been compared with a baseline and each other to find the best performing models on this data set. In conclusion, REPTree, OneR, and Support Vector Machines (SVM) with Sequential Minimal Optimization (SMO) algorithms achieved top performance in forecasting requirements engineers’ CFP training need.

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“…Accuracy in estimation is a crucial factor for planning software development to evade budget overruns and tardy delivery of software. Estimation of test effort along with development is considered crucial for apprehending quality software [3]. Development of mobile software is considered different from developing traditional software pertaining to its distinctive features such as limited memory, processing power, small and multiple input interface, multiple connections, bandwidth factor, a lower battery, etc.…”

Section: Introductionmentioning

confidence: 99%

Effort Estimation in Traditional and Agile Mobile Application Development & Testing

Kaur¹,

Kaur²

2018

IJEECS

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Smartphones<em>/</em>mobile devices are enduring all the aspects of human life. With the significant increase in demand for applications running on smartphones/mobile devices, developers and testers are anticipated to deliver high quality, on time and within budget applications. The estimation of development and testing provides a baseline and act as a tracking gear for stakeholders and developers. There are various approaches for estimation of traditional software development. But mobile applications are considered different from traditional software such as from those running on desktop, laptop or on the web. Many traditional estimation techniques used for these software are adapted to mobile domain. With agile software development (ASD) methodology, the scenario of development and estimation has changed drastically and so as mobile app development and estimation. This paper provides a Systematic Literature Review (SLR) on traditional estimation techniques and agile estimation techniques applied in mobile software/application. Also, effort attributes and accuracy parameters for estimation in mobile apps are presented. However, to date, there are very fewer studies done on the mobile application estimation domain using agile methodology.

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Early Test Effort Prediction using UML Diagrams

Abstract: Abstract

Cited by 15 publications

References 6 publications

Comparative Analysis of Various Testing Techniques used for Aspect-Oriented Software System

Comparative Analysis of Various Testing Techniques used for Aspect-Oriented Software System

Using Data Mining to Identify COSMIC Function Point Measurement Competence

Effort Estimation in Traditional and Agile Mobile Application Development & Testing

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