This paper introduces an approach to locating dependence structures in a program by searching the space of the powerset of the set of all possible program slices. The paper formulates this problem as a search-based software engineering problem. To evaluate the approach, the paper introduces an instance of a search-based slicing problem concerned with locating sets of slices that decompose a program into a set of covering slices that minimize inter-slice overlap. The paper reports the result of an empirical study of algorithm performance and result-similarity for Hill Climbing, Genetic, Random Search and Greedy Algorithms applied to a set of 12 C programs.