If you are a software developer, manager, or maintainer, quality is often on your mind. But what do you really mean by software quality? Is your definition adequate? Is the software you produce better or worse than you would like it to be? In this special issue, we put software quality on trial, examining both the definition and evaluation of our software products and processes.
In this paper we propose a framework for validating software measurement. We start by defining a measurement structure model that identifies the elementary component of measures and the measurement process, and then consider five other models involved in measurement: unit definition models, instrumentation models, attribute relationship models, measurement protocols and entity population models. We consider a number of measures from the viewpoint of our measurement validation framework and identify a number of shortcomings; in particular we identify a number of problems with the construction of function points. We also compare our view of measurement validation with ideas presented by other researchers and identify a number of areas of disagreement. Finally, we suggest several rules that practitioners and researchers can use to avoid measurement problems, including the use of measurement vectors rather than artificially contrived scalars.
Case studies help industry evaluate the benefits of methods and tools and provide a cost-effective way to ensure that process changes provide the desired results. However, unlike fomal experiments and surveys, case studies do not have a well-understood theoretical basis. This article provides guidelinesfor organizing and anahzing case studies so that they produce meaning@ results.
Although surveys are an extremely common research method, surveybased research is not an easy option. In this chapter, we use examples of three software engineering surveys to illustrate the advantages and pitfalls of using surveys. We discuss the six most important stages in survey-based research: setting the survey's objectives; selecting the most appropriate survey design; constructing the survey instrument (concentrating on self-administered questionnaires); assessing the reliability and validity of the survey instrument; administering the instrument; and, finally, analysing the collected data. This chapter provides only an introduction to survey-based research; readers should consult the referenced literature for more detailed advice.
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