Programming experience is an important confound- ing parameter in controlled experiments regarding program comprehension. In literature, ways to measure or control programming experience vary. Often, researchers neglect it or do not specify how they controlled it. We set out to find a well-defined understanding of programming experience and a way to measure it. From published comprehension experiments, we extracted questions that assess programming experience. In a controlled ex- periment, we compare the answers of 128 students to these ques- tions with their performance in solving program-comprehension tasks. We found that self estimation seems to be a reliable way to measure programming experience. Furthermore, we applied exploratory factor analysis to extract a model of programming experience. With our analysis, we initiate a path toward mea- suring programming experience with a valid and reliable tool, so that we can control its influence on program comprehension.
Tue 17 MayDisplayed time zone: Eastern Time (US & Canada) change
03:50 - 04:50
MIP TalkResearch at ICPC room
Chair(s): Gabriele Bavota Software Institute, USI Università della Svizzera italiana, Arie van Deursen Delft University of Technology, Netherlands
This event will be held in Zoom. Please check Midspace for the link.
|Measuring programming experience|
Janet Siegmund Chemnitz University of Technology, Christian Kästner Carnegie Mellon University, Jörg Liebig , Sven Apel Saarland University, Stefan Hanenberg paluno – The Ruhr Institute for Software Technology, University of Duisburg-Essen, Essen