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Estimating Worst-case Resource Usage by Resource-usage-aware Fuzzing

Part of the Lecture Notes in Computer Science book series (LNCS,volume 13241)


Worst-case resource usage provides a useful guidance in the design, configuration and deployment of software, especially when it runs under a context with limited amount of resources. Static resource-bound analysis can provide sound upper bounds of worst-case resource usage but may provide too conservative, even unbounded, results. In this paper, we present a resource-usage-aware fuzzing approach to estimate worst-case resource usage. The key idea is to guide the fuzzing process using resource-usage amount together with resource-usage relevant coverage. Moreover, we leverage semantic patch to make use of static analysis information (including control-flow, function-call, etc.) to instrument the original program, for the sake of aiding the subsequent fuzzing. We have conducted experiments to estimate worst-case resource usage of various resources in real-world programs, including heap memory, stack depths, sockets, user-defined resources, etc. The preliminary experimental results show the promising ability of our approach in estimating worst-case resource usage in real-world programs, compared with two state-of-the-art fuzzing tools (AFL and MemLock).


  • Fuzzing
  • Resource Usage
  • Static Analysis

This work is supported by the National Key R&D Program of China (No. 2017YFB1001802), and the NSFC (Nos. 61872445, 62032024).


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Correspondence to Liqian Chen or Dengping Wei .

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Chen, L., Huang, R., Luo, D., Ma, C., Wei, D., Wang, J. (2022). Estimating Worst-case Resource Usage by Resource-usage-aware Fuzzing. In: Johnsen, E.B., Wimmer, M. (eds) Fundamental Approaches to Software Engineering. FASE 2022. Lecture Notes in Computer Science, vol 13241. Springer, Cham.

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