## 2 Background
### Sizing Software with COSMIC--ISO 19761
\begin{table}
\begin{tabular}{c c c} \hline \hline \multicolumn{2}{c}{**Application in Web Development**} & \multicolumn{1}{c}{**Application in Web Analytics**} \\ \hline  & The traditional metrics for estimating web & Web analytics involve complex \\  & application size, such as the number of web pages, & interactions; data flows and user behavior \\  & lines of code, and media files, are widely & tracking are not adequately captured by \\
**Limitations of** & development effort. These fail to account for the & basic counting metrics such as the number \\
**Traditional** & functional complexity and variability in web & of pages, lines of code, or media files; \\
**Metrics** & applications, leading to unreliable estimates. This & applying similar simplistic metrics to web \\  & highlights the need for more sophisticated & analytics implementation would likely \\  & approaches that can better capture the true scope & lead to inaccurate and \\  & and functionality of web projects. & unreliable assessments. \\ \hline  & The literature demonstrates the emergence of more & There is no reported usage yet of COSMIC \\
**Emergence of** & advanced functional size measurement techniques, & FSM in the context of web analytics \\
**Functional Size** & particularly using the COSMIC method. COSMIC & implementation projects. \\
**Measurement** & has been shown to be more adaptable and effective & Web analytics implementation should be \\
**(FSM)** & in measuring the functional size of web & sized using function-based measurement \\  & applications, offering a more reliable basis for & approaches, similar to how COSMIC is \\  & estimating development effort. & applied to web applications. \\ \hline  & Researchers have worked on adapting and refining & \\
**Adaptation and** & the COSMIC method to specific types of web & Research is needed to explore how to \\  & applications such as the Object-Oriented & measure web analytics implementations \\
**Refinement of** & Hypermedia (OO-H) method or the UML-based & effectively with functional size \\ FSM & Web Engineering (UWE) approach. These & measurement (FSM) approaches \\  & adaptations ensure the accurate application of & such as COSMIC. \\  & FSM in the unique context of web applications. & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Key insights from the literature on web development and web analytics implementation. application) of the software to be measured are identified. The outcome of this phase is the Software Context Model, which includes components such as functional users (e.g., software or hardware devices), the software being measured, and persistent storage. 2. Mapping Phase: This is the process that translates each Functional User Requirement (FUR) into the format required by the COSMIC Generic Model of Software using concepts, such as the following. * A _Triggering Event_ is the action of a functional user of software that initiates one or more functional processes. * A _Data Group_ is a distinct, non-empty, and unordered set of data attributes, with each attribute describing a complementary aspect of the same object of interest. * A _Data Attribute_ is the smallest piece of information within an identified data group that carries meaning from the perspective of a relevant FUR. As shown in Figure 2, COSMIC data movements are defined as follows: * _Entry (E)_ transfers a data group from a functional user across the boundary into a functional process, where it is needed. * An _Exit (X)_ transfers a data group from a functional process across the boundary to the functional user that requires it. * A _Read (R)_ retrieves a data group from persistent storage within a functional process that requires it. * _Write (W)_ stores a data group from within a functional process into persistent storage. 3. Measurement Phase: This involves identifying and counting the data movements within each functional process. Each data movement is counted as one COSMIC Function Point (CFP).