Inferring Message Flows From System Communication Traces

TL;DR

This paper presents a new automated approach for inferring message flow specifications from system communication traces, improving accuracy and efficiency for SoC validation and debugging.

Contribution

It introduces a novel method utilizing acceptance ratio and essential causalities to enhance message flow inference from system traces.

Findings

Achieves higher accuracy than previous methods on synthetic and real traces.

Uses acceptance ratio as a new metric for evaluating inferred specifications.

Demonstrates practical applicability through real-world use cases.

Abstract

This paper proposes a novel method for automatically inferring message flow specifications from the communication traces of a system-on-chip (SoC) design that captures messages exchanged among the components during a system execution. The inferred message flows characterize the communication and coordination of components in a system design for realizing various system functions, and they are essential for SoC validation and debugging. The proposed method relieves the burden of manual development and maintenance of such specifications on human designers. Our method also uses a new accuracy metric, \emph{acceptance ratio}, to evaluate the quality of the mined specifications instead of the specification size often used in the previous work, enabling more accurate specifications to be mined. Furthermore, this paper introduces the concept of essential causalities to enhance the accuracy of the message flow mining and accelerate the mining process. The effectiveness of the proposed method is evaluated on both synthetic traces and traces generated from executing several system models in GEM5. In both cases, the proposed method achieves superior accuracies compared to a previous approach. Additionally, this paper includes some practical use cases.