Predictive Software Measures Based on Formal Z Specifications
A means of predicting software costs
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The success of software development projects depends highly on meeting the assigned schedule and budget of the project which are often defined in terms of a project plan. Estimation is the basis for planning; therefore, having a reliable way of estimating effort needed to perform the tasks is a must for a reliable project plan. Already in 1987, Samson, Nevill and Dugard, showed that there is a strong and direct influence of formal specification metrics onto the effort needed for implementation. Since then, there has been some progress in various aspects of formal specifications; the introducti...
The success of software development projects depends highly on meeting the assigned schedule and budget of the project which are often defined in terms of a project plan. Estimation is the basis for planning; therefore, having a reliable way of estimating effort needed to perform the tasks is a must for a reliable project plan. Already in 1987, Samson, Nevill and Dugard, showed that there is a strong and direct influence of formal specification metrics onto the effort needed for implementation. Since then, there has been some progress in various aspects of formal specifications; the introduction of specification slicing methods, slice-based specification metrics, and methods for visualization of specifications has opened new ways for measuring properties of specifications with more metrics. Nevertheless, there hasn t been much progress in the field of cost estimation using recent achievements of formal specifications. The main focus in this work is to examine if there is a correlation between formal Z specification measures and implementation related measures. In concise, this work tries to explain the correlation between the measures in specifications and code.
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