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Implicit Computational Complexity (ICC) drives better understanding ofcomplexity classes, but it also guides the development of resources-awarelanguages and static source code analyzers. Among the methods developed, themwp-flow analysis certifies polynomial bounds on the size of the valuesmanipulated by an imperative program. This result is obtained by bounding thetransitions between states instead of focusing on states in isolation, as moststatic analyzers do, and is not concerned with termination or tight bounds onvalues. Those differences, along with its built-in compositionality, make themwp-flow analysis a good target for determining how ICC-inspired techniquesdiverge compared with more traditional static analysis methods. This paper'scontributions are threefold: we fine-tune the internal machinery of theoriginal analysis to make it tractable in practice; we extend the analysis tofunction calls and leverage its machinery to compute the result of the analysisefficiently; and we implement the resulting analysis as a lightweight tool toautomatically perform data-size analysis of C programs. This documented effortprepares and enables the development of certified complexity analysis, bytransforming a costly analysis into a tractable program, that furthermoredecorrelates the problem of deciding if a bound exist with the problem ofcomputing it.

mwp-Analysis Improvement and Implementation: Realizing Implicit Computational Complexity