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Performance Estimation Using Symbolic Data

  • Jian Zhang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8051)

Abstract

Symbolic execution is a useful technique in formal verification and testing. In this paper, we propose to use it to estimate the performance of programs. We first extract a set of paths (either randomly or systematically) from the program, and then obtain a weighted average of the performance of the paths. The weight of a path is the number of input data that drive the program to execute along the path, or the size of the input space that corresponds to the path. As compared with traditional benchmarking, the proposed approach has the benefit that it uses more points in the input space. Thus it is more representative in some sense. We illustrate the new approach with a sorting algorithm and a selection algorithm.

Keywords

Input Space Performance Estimation Array Element Symbolic Data Sorting Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Jian Zhang
    • 1
  1. 1.State Key Laboratory of Computer Science, Institute of SoftwareChinese Academy of SciencesBeijingChina

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