A Highly Scalable, Hybrid, Cross-Platform Timing Analysis Framework Providing Accurate Differential Throughput Estimation via Instruction-Level Tracing

Min-Yih Hsu, Felicitas Hetzelt, David Gens, Michael Maitland, Michael Franz. A Highly Scalable, Hybrid, Cross-Platform Timing Analysis Framework Providing Accurate Differential Throughput Estimation via Instruction-Level Tracing. In Satish Chandra 0001, Kelly Blincoe, Paolo Tonella, editors, Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, ESEC/FSE 2023, San Francisco, CA, USA, December 3-9, 2023. pages 821-831, ACM, 2023. [doi]

@inproceedings{HsuHGMF23,
  title = {A Highly Scalable, Hybrid, Cross-Platform Timing Analysis Framework Providing Accurate Differential Throughput Estimation via Instruction-Level Tracing},
  author = {Min-Yih Hsu and Felicitas Hetzelt and David Gens and Michael Maitland and Michael Franz},
  year = {2023},
  doi = {10.1145/3611643.3616246},
  url = {https://doi.org/10.1145/3611643.3616246},
  researchr = {https://researchr.org/publication/HsuHGMF23},
  cites = {0},
  citedby = {0},
  pages = {821-831},
  booktitle = {Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, ESEC/FSE 2023, San Francisco, CA, USA, December 3-9, 2023},
  editor = {Satish Chandra 0001 and Kelly Blincoe and Paolo Tonella},
  publisher = {ACM},
}