Abstract
During programming, end-user developers constantly go to search engines to seek for information. The search engine is of significant help since it ranks the webpage links according to relevance. However, the time cost of foraging a webpage also affects if and how soon a developer can obtain a satisfying answer. In this paper, we use operationalizable constructs from Information Foraging Theory to identify two features: information accumulation and information amount for a webpage, which we hypothesize could assist developers in selecting appropriate webpages. We then invited 20 participants to perform a lab experiment of two software change tasks. The results supported our hypothesis by two findings. When having the tool support, the participants used less task completion time, and tended to visit more easy-to-forage webpages.