Interest has grown recently in the application of computational and statistical tools to problems in the analysis of algorithms. In many algorithmic domains, worst-case bounds are too pessimistic and tractable probabilistic models too unrealistic to provide meaningful predictions of practical algorithmic performance. Experimental approaches can provide knowledge where purely analytical methods fail and can provide insights to motivate and guide deeper...