Profiling k-Iteration Paths : A Generalization of the Ball-Larus Profiling Algorithm

Abstract

The Ball-Larus path-profiling algorithm is an efficient technique to collect acyclic path frequencies of a program. However, longer paths — those extending across loop iterations — describe the runtime behaviour of programs better. We generalize the Ball-Larus profiling algorithm for profiling k-iteration paths — paths that can span up to to k iterations of a loop. We show that it is possible to number such k-iteration paths perfectly, thus allowing for an efficient profiling algorithm for such longer paths. We also describe a scheme for mixed-mode profiling: profiling different parts of a procedure with different path lengths. Experimental results show that k-iteration profiling is realistic.