Many software-engineering tasks require developers to understand the history and evolution of source code. However, today’s software-development techniques and tools are not well suited for the easy and efficient procurement of such information. In this paper, we present an approach called history slicing that can automatically identify a minimal number of code modifications, across any number of revisions, for any arbitrary segment of source code at fine granularity. We also present our implementation of history slicing, Chronos, that includes a novel visualization of the entire evolution for the code of interest. We provide two experiments: one experiment automatically computes 16,000 history slices to determine the benefit brought by various levels of automation, and another experiment that assesses the practical implications of history slicing for actual developers using the technique for actual software-maintenance tasks that involve code evolution. The experiments show that history slicing offered drastic improvements over the conventional techniques in three ways: (1) the amount of information needed to be examined and traced by developers was reduced by up to three orders of magnitude; (2) the correctness of developers attempting to solve software-maintenance tasks was more than doubled; and (3) the time to completion of these software-maintenance tasks was almost halved.