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
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.