May 22, 2020
Data Measurement and Analysis for Software Engineers
—A look at measurement and its application in software engineering.
In Data Measurement and Analysis for Software Engineers, I go through Part 1 of a talk by Dennis J. Frailey. Part 1 describes scales of measurement and the importance of understanding which statistical operations make sense on those scales. Scales are important because they define the properties of what is being measured.
Part 2 looks at basic analysis techniques for software engineering and what makes a good measurement process. Importantly,
If you only measure the code, you will probably not really understand your software or its development process.
Why? Because many software products are not code. They include specifications, design models, tests, etc. An error in a software product can result in errors in those that depend upon it.
Measurement smells:
- Requirements are not measurable.
- Activities are not measured.
- Software quality attributes are not measured or modeled.
- Performance of tools and methods employed are not based on factual data.
The countermeasure to these smells is the measurement process. It
- establishes a measurement program,
- implements a measurement program and
- evaluates the measurements.
The International Standard for Software Measurement Processes (ISO/IEC/IEEE 15939) describes describes a set of criteria for a good measuring process. It does not define a process but tells you what a good process should be like.
A good measurement process requires establishing what your information needs are. Identifying what to measure is the subject of The Goal/Question/Metric (GQM) Paradigm.
The webinar walks through a process for metrics.
- Organize the base measures (stuff we measure) by refining or compressing it. This ensures that data comprising base measures is consistent.
- Compute derived measures from base measures. This ensures that derived measures are directed at fulfilling information needs.
Base measures must be established with consideration of their scales of measure. This determines the meaningful statistic calculations as part of the derived measures.
The use of probability distributions and statistics is the subject of the third webinar. This includes discrete and continuous functions.
