Software Engineering169-Metrics for object oriented projects

The job of the project manager is to plan, coordinate, track, and control a software project. We  already discussed some of the special issues associated with management of OO projects. But what about measurement? Are there specialized OO metrics that can be used by the project manager to provide additional insight into progress?8 The answer, of course, is, “Yes.”

The first activity performed by the project manager is planning, and one of the early planning tasks is estimation. Recalling the evolutionary process model, planning is revisited after each iteration of the software. Therefore, the plan (and its project estimates) are revisited after each iteration of OOA, OOD, and even OOP.

A key issue that faces a project manager during planning is an estimate of the implemented size of the software. Size is directly proportional to effort and duration. The following OO metrics can provide insight into software size:

Number of scenario scripts (NSS). The number of scenario scripts or use-cases  is directly proportional to the number of classes required to meet requirements; the number of states for each class; and the number of methods, attributes, and collaborations. NSS is a strong indicator of program size.

Number of key classes (NKC). A key class focuses directly on the business domain for the problem and will have a lower probability of being implemented via reuse.9 For this reason, high values for NKC indicate substantial development work. Lorenz and Kidd  suggest that between 20 and 40 percent of all classes in a typical OO system are key classes. The remainder support infrastructure (GUI, communications, databases, etc.).

Number of subsystems (NSUB). The number of subsystems provides insight into resource allocation, scheduling (with particular emphasis on parallel development) and overall integration effort.

The metrics NSS, NKC, and NSUB can be collected for past OO projects and are related to the effort expended on the project as a whole and on individual process activities (e.g., OOA, OOD, OOP, and OOT). These data can also be used along with the design metrics discussed earlier in this chapter to compute “productivity metrics” such as average number of classes per developer or average methods per personmonth. Collectively, these metrics can be used to estimate effort, duration, staffing, and other information for the current project.
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