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CS605 - Software Engineering II - Lecture Handout 16

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Interpreting Measurements

A good metric system is the one which is simple and cheap and at the same time adds a lot of value for the management. Following are some of the examples that can be used for effective project control and management.

We can collect data about the defects reported, and defects fixed and plot them in the following manner, with their difference showing the defects yet to be fixed. This can give us useful information about the state of the product. If the gap between the defects reported and defects fixed is increasing, then it means that the product is in unstable condition. On the other hand if this gap is decreasing then we can say that the product is in a stable condition and we can plan for shipment.

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CS605 - Software Engineering II - Lecture Handout 15

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Statistical Control Techniques – control charts

Same process metrics vary from project to project. We have to determine whether the trend is statistically valid or not. We also need to determine what changes are meaningful. A graphical technique known as control charts is used to determine this.

This technique was initially developed for manufacturing processes in the 1920’s by Walter Shewart and is still very applicable even in disciples like software engineering. Control charts are of two types: moving range control chart and individual control chart. This technique enables individuals interested in software process improvement to determine whether the dispersion (variability) and “location” (moving average) of process metrics are stable (i.e. the process exhibits only natural or controlled changes) or unstable (i.e. the process exhibits out-of-control changes and metrics cannot be used to predict performance).

Read more: CS605 - Software Engineering II - Lecture Handout 15