A parametric effort estimation model for mobile apps

Shahwaiz, Syed Ahmad; Malik, Ali Afzal; Sabahat, Nosheen

doi:10.1109/inmic.2016.7840114

Cited by 13 publications

(10 citation statements)

References 8 publications

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“…The value of SSR equals 49743.2 for (7), which is more than 10 times the corresponding amount for the model (1). The R 2 , MMRE, and PRED(0.25) values equal 0.826, 0.180, and 0.690 respectively for (7). These values of the standard metrics are worse than the corresponding values for the model (1) based on the Johnson four-variate transformation for the SB family.…”

Section: Comparison Of Regression Modelsmentioning

confidence: 79%

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Estimating the Efforts of Mobile Application Development in the Planning Phase Using Nonlinear Regression Analysis

Prykhodko

Knyrik

2020

Applied Computer Systems

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The authors consider the construction of a nonlinear multiple regression model, its confidence and prediction intervals to evaluate the efforts of mobile application development in the planning phase based on the multivariate normalizing transformation and outlier detection. The constructed model is compared to the linear regression model and nonlinear regression models based on the univariate transformations, such as the decimal logarithm, Box–Cox, and Johnson transformation. This model, in comparison with other regression models, has better prediction accuracy.

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Section: Comparison Of Regression Modelsmentioning

confidence: 79%

“…These values of the standard metrics are worse than the corresponding values for the model (1) based on the Johnson four-variate transformation for the SB family. Besides, the value of PRED(0.25) for (7) indicates the low percentage of prediction of this model (7).…”

Section: Comparison Of Regression Modelsmentioning

confidence: 99%

Estimating the Efforts of Mobile Application Development in the Planning Phase Using Nonlinear Regression Analysis

Prykhodko

Knyrik

2020

Applied Computer Systems

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“…Moreover, Shahwaiz, Malik, and Sabahat [43] proposed a parametric model to estimate the effort needed to create mobile application software. Shahwaiz identified 20 effort predictors (e.g.…”

Section: Technique Using Metrics/cost Driversmentioning

confidence: 99%

Effort Estimation across Mobile App Platforms using Agile Processes: A Systematic Literature Review

Altaleb¹,

Gravell²

2018

JSW

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Abstract:It is predicted that smartphone numbers will increase to 2.8B in 2018, up from around 2B in 2016. Moreover, revenue from application stores is predicted to reach $189B by 2020, up from $88.3B in 2016 1 . Software effort and size estimation are essential when it comes to project managers being able to manage and plan a project so as to prevent it from failing. The planning and development of mobile applications differs from other traditional software applications due to the characteristics of the mobile environment, high autonomy requirements, market competition, and many other constraints. Therefore, this paper presents the results of a Systematic Literature Review (SLR) concerning effort and size estimation models in mobile application development; this is followed by a summary of estimation techniques used across mobile apps. In particular, we focus on the software estimation models that are applicable to the Agile Software Development (ASD) process. The aim of this SLR is to provide researchers and practitioners with an overview of the current state-of-the-art software estimation techniques used in mobile applications. At the end of this review, some suggestions, research gaps and possible future work will be presented.

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“…Other types of estimation techniques identified are Function Point Analysis [29,30] and Use Case Point [31] which is algorithmic-based models that measure functional, technical factors and environmental factors for estimation. Regression-Based technique [32] uses a parametric model based on effort predictors and data points collected through an online questionnaire which are further used in the regression model. Delphi method [33] is based on experience to estimate the effort whereas Architecture Based estimation model [34] for reliability and testing estimation of the mobile application is proposed and the case study was conducted in two companies.…”

Section: Traditional Techniques For Estimating Mobile Application Devmentioning

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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A parametric effort estimation model for mobile apps

Cited by 13 publications

References 8 publications

Estimating the Efforts of Mobile Application Development in the Planning Phase Using Nonlinear Regression Analysis

Estimating the Efforts of Mobile Application Development in the Planning Phase Using Nonlinear Regression Analysis

Effort Estimation across Mobile App Platforms using Agile Processes: A Systematic Literature Review

Effort Estimation in Traditional and Agile Mobile Application Development & Testing

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