Software engineering involves a blend of non-technical as well as technical issues that often have to be taken into account in the design of empirical studies. In particular, the behavior of people is an integral part of software development and maintenance. This aspect of our subject presents complexities and challenges for the empirical researcher. In many other disciplines, qualitative research methods have been developed and are commonly used to handle the complexity of issues involving people performing tasks in their workplace. Studies attempting to capture human behavior as it relates to software engineering are increasing and, not surprisingly, are increasingly employing qualitative methods.

Qualitative data are data represented as text and pictures, not numbers (Gilgun, 1992). The principal advantage of using qualitative methods is that they force the researcher to delve into the complexity of the problem rather than abstract it away. Thus the results are richer and more informative. They help to answer questions that involve variables that are difficult to quantify (particularly human characteristics such as motivation, perception, and experience). They are also used to answer the "why" to questions already addressed by quantitative research. There are drawbacks, however. Qualitative analysis is generally more labor-intensive and exhausting than quantitative analysis. Qualitative results often are considered "softer" and "fuzzier" than quantitative results, especially in technical communities like ours. They are more difficult to summarize or simplify. But then, so are the problems we study in software engineering.

Adapted from "Chapter 2: Qualitative Methods", Carolyn Seaman. In Guide to Advanced Empirical Software Engineering, Forrest Shull, Janice Singer, and Dag I.K. Sjoberg, eds. Springer 2008.