Although gender differences in a technological world are receiving significant research attention, much of the research and practice has aimed at how society and education can impact the successes and retention of female computer science professionals-but the possibility of gender issues within software has received almost no attention. If gender issues exist with some types of software features, it is possible that accommodating them by changing these features can increase effectiveness, but only if we know what these issues are. In this paper, we empirically investigate gender differences for end users in the context of debugging spreadsheets. Our results uncover significant gender differences in self-efficacy and feature acceptance, with females exhibiting lower self-efficacy and lower feature acceptance. The results also show that these differences can significantly reduce females' effectiveness.