DeltaPath: Precise and Scalable Calling Context Encoding

  • Authors:

  • Qiang Zeng;Junghwan Rhee;Hui Zhang;Nipun Arora;Guofei Jiang;Peng Liu

  • Affiliations:

  • Penn State University;NEC Laboratories America;NEC Laboratories America;NEC Laboratories America;NEC Laboratories America;Penn State University

  • Venue:
  • Proceedings of Annual IEEE/ACM International Symposium on Code Generation and Optimization
  • Year:
  • 2014

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Abstract

Calling context provides important information for a large range of applications, such as event logging, profiling, debugging, anomaly detection, and performance optimization. While some techniques have been proposed to track calling context efficiently, they lack a reliable and precise decoding capability; or they work only under restricted conditions, that is, small programs without object-oriented programming or dynamic component loading. These shortcomings have limited the application of calling context tracking in practice. We propose an encoding technique without those limitations: it provides precise and reliable decoding, supports large-sized programs, both procedural and objected-oriented ones, and can cope with dynamic class/library loading. The technique thus enables calling context tracking in a wide variety of scenarios. The evaluation on SPECjvm shows that its efficiency is comparable with that of the state-of-the-art approach while our technique provides precise decoding and demonstrates scalability and flexibility.