2014 Volume 22 Issue 2 Pages 202-209
In this paper we construct and analyze a crowdsourcing-based bug detection model in which strategic players select code and compete in bug detection contests. We model the contests as all-pay auctions, and our focus is on addressing the low efficiency problem in bug detection by division strategy. Our study shows that the division strategy can control two features of the bug detection contest, in terms of the expected reward classes and the scales of skill levels, by intentionally assembling players with particular skill distribution in one division. In this way, division strategy is able to determine the players' strategic behaviors on code selection, and thus improve the bug detection efficiency. We analyze the division strategy characterized by skill mixing degree and skill similarity degree and find an explicit correspondence between the division strategy and the bug detection efficiency. Based on our simulation results, we verified that the skill mixing degree, serving as determinant factor of division strategy, controls the trend of the bug detection efficiency, and skill similarity degree plays an important role in indicating the shape of the bug detection efficiency.
