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Data Structure MetricsEssentially the need for software development and other activities are to process data. Some data is input to a system, program or module; some data may be used internally, and some data is the output from a system, program, or module. Example:
That's why an important set of metrics which capture in the amount of data input, processed in an output form software. A count of this data structure is called Data Structured Metrics. In these concentrations is on variables (and given constant) within each module & ignores the input-output dependencies. There are some Data Structure metrics to compute the effort and time required to complete the project. There metrics are:
1. The Amount of Data: To measure the amount of Data, there are further many different metrics, and these are:
2. The Usage of data within a Module: The measure this metric, the average numbers of live variables are computed. A variable is live from its first to its last references within the procedure. ![]() For Example: If we want to characterize the average number of live variables for a program having modules, we can use this equation. ![]() Where (LV) is the average live variable metric computed from the ith module. This equation could compute the average span size (SP) for a program of n spans. ![]() 3. Program weakness: Program weakness depends on its Modules weakness. If Modules are weak(less Cohesive), then it increases the effort and time metrics required to complete the project. ![]() Module Weakness (WM) = LV* γ A program is normally a combination of various modules; hence, program weakness can be a useful measure and is defined as: ![]() Where WMi: Weakness of the ith module WP: Weakness of the program m: No of modules in the program 4.There Sharing of Data among Module: As the data sharing between the Modules increases (higher Coupling), no parameter passing between Modules also increased, As a result, more effort and time are required to complete the project. So Sharing Data among Module is an important metrics to calculate effort and time. ![]() ![]()
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