Software Estimation Framework for Mobile Application Projects

Software Estimation Framework for Mobile Application Projects

Shailesh Kumar (PES University, Bengaluru, India) and Anant R. Koppar (PES University, Bengaluru, India)
DOI: 10.4018/IJPMAT.2019070102
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As mobile devices are becoming the primary access channels for information, the authors need to have accurate effort estimation model for mobile application projects. In this paper the authors discuss “Mobile application estimation framework” that was designed based on 14 mobile application projects and was validated against 5 mobile application projects. In this paper the authors discuss the estimation framework for both native/hybrid mobile application projects and mobile web application projects. The proposed “Mobile application estimation framework” provides comprehensive coverage for various factors involved in mobile estimation such as layer-wise components, horizontal components and others. The estimation framework also considers the cost drivers and is used as effort adjustment factor. The proposed mobile application estimation framework achieved the MMRE of 0.207 with pred (0.3) of 80%.
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In this section we will look at the existing methods for estimating the mobile application projects. The state of the art mobile estimation methods can be categorized into three main categories:

  • Effort Estimation based on functionality: In this category, we include estimations based on functional size of the mobile app. COSMIC functional size, use case information and functional size estimation are included in this category;

  • Effort Estimation based on cost drivers: In this category we include various cost drivers such as UML diagram, supported platforms etc.;

  • Effort estimation based on other factors: In this category we include analogy based estimation, experience based estimation, agile method based estimation.

Effort Estimation Based on Functionality

D'Avanzo, Ferrucci, Gravino, and Salza, (2015) proposed COSMIC functional size for mobile application estimation using lines of code (LOC) and number of bytes of source code and byte code. Function size quantifies the value of functional requirements (Abran et al., 2015) Functional size estimation (FSM) is also proposed by other researchers for mobile application estimation (Abdullah, Rusli, & Ibrahim, 2014; van Heeringen & Van Gorp, 2014; Nitze, Schmietendorf, & Dumke, 2014; Preuss, 2012; Preuss, 2014; Sethumadhavan, 2011; Souza & Aquino, 2014). Francese, Gravino, Risi, Scanniello, and Tortora (2015) use information such as number of actors, number of use cases, number of classes from the requirements specification documents and use linear regression to build the estimation model. Lusky, Powilat, and Böhm, (2017) propose an experience based approach that uses variations in mobile app features based on roles, perspectives and complexity levels for estimation. Kaur and Kaur (2019) propose use case point (UCP) based estimation model.

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