Haplotype inference by pure parsimony (HIPP) is a well-known paradigm for haplotype inference. In order to assess the biological
significance of this paradigm, we generalize the problem of HIPP to the problem of finding all optimal solutions, which we
call complete HIPP. We study intrinsic haplotype features, such as backbone haplotypes and fat genotypes as well as equal
columns and decomposability. We explicitly exploit these features in three computational approaches which are based on integer
linear programming, depth-first branch-and-bound, and a hybrid algorithm that draws on the diverse strengths of the first
two approaches. Our experimental analysis shows that our optimized algorithms are significantly superior to the baseline algorithms,
often with orders of magnitude faster running time. Finally, our experiments provide some useful insights to the intrinsic
features of this interesting problem.