Computer Science and Engineering, Department of

 

Date of this Version

2007

Comments

Published in First International Symposium on Empirical Software Engineering and Measurement. Copyright 2007 IEEE. Used by permission.

Abstract

While much of the software that people depend on is written by professional software engineers, increasingly, important applications are being created by non-professional (end-user) programmers. Using tools such as spreadsheet environments and web authoring tools, these programmers are creating software that is being used to support significant activities and inform decisions. Such software needs to work dependably and increase user productivity, but evidence shows that it frequently does not. For example, studies have shown that a large percentage of the spreadsheets created by end-users contain faults, and data suggests that time spent maintaining web macros may actually impede their users’ overall efforts.

In recent years researchers have begun to address this problem, considering various approaches to adapting software engineering techniques to the realm of end-user programming. For example, researchers have sought ways to help end users test and debug spreadsheets, and to increase productivity in web macros by combining them with various software engineering devices. To make progress in this area, researchers are turning to empirical studies, in order to investigate new approaches, understand the factors that influence them, and better understand issues related to end user programmers themselves.

In this talk I will present recent work being done in end-user software engineering, with a particular focus on the state of the art of empirical research in the area. I will show that there is a pressing need for further empirical work in this context, and that there are interesting questions that researchers from the ESEM community could help to answer. For example, how are end-users different from programmers, and how does that affect how we conduct the research? (Are there assumptions we make when doing studies with programmers that do not hold with end-users? What are the threats to validity when, say, we use CS students as subjects in end-user studies?) As another example, how are end-users different from each other and how does that affect study results? (The end-user community is much more diverse than the professional programmer community. What are the important context variables one needs to capture when studying them?) A concerted effort by the ESEM community on such issues could result in a substantial impact on society as a whole, and on the everyday lives of many people.

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