Software product lines (SPLs) are commonly developed using annotative approaches such as conditional compilation that come with an inherent risk of constructing erroneous products. For this reason, it is essential to be able to analyze SPLs. However, as dataflow analysis techniques are not able to deal with SPLs, developers must generate and analyze all valid methods individually, which is expensive for non-trivial SPLs. In this paper, we demonstrate how to take any standard intraprocedural dataflow analysis and automatically turn it into a feature-sensitive dataflow analysis in three different ways. All are capable of analyzing all valid methods of an SPL without having to generate all of them explicitly. We have implemented all analyses as extensions of SOOT's intraprocedural dataflow analysis framework and experimentally evaluated their performance and memory characteristics on four qualitatively different SPLs. The results indicate that the feature-sensitive analyses are on average 5.6 times faster than the brute force approach on our SPLs, and that they have different time and space tradeoffs.