Document Open Access Logo

Static Analysis of Shape in TensorFlow Programs (Artifact)

Authors Sifis Lagouvardos, Julian Dolby, Neville Grech, Anastasios Antoniadis, Yannis Smaragdakis



PDF
Thumbnail PDF

Artifact Description

DARTS.6.2.6.pdf
  • Filesize: 330 kB
  • 3 pages

Document Identifiers

Author Details

Sifis Lagouvardos
  • University of Athens, Greece
Julian Dolby
  • IBM Research, Yorktown Heights, NY, USA
Neville Grech
  • University of Athens, Greece
Anastasios Antoniadis
  • University of Athens, Greece
Yannis Smaragdakis
  • University of Athens, Greece

Cite AsGet BibTex

Sifis Lagouvardos, Julian Dolby, Neville Grech, Anastasios Antoniadis, and Yannis Smaragdakis. Static Analysis of Shape in TensorFlow Programs (Artifact). In Special Issue of the 34th European Conference on Object-Oriented Programming (ECOOP 2020). Dagstuhl Artifacts Series (DARTS), Volume 6, Issue 2, pp. 6:1-6:3, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2020)
https://doi.org/10.4230/DARTS.6.2.6

Artifact

Abstract

These instructions are intended for using the artifact for our ECOOP'20 paper entitled "Static Analysis of Shape in TensorFlow Programs". They can be used to run Pythia - the tool implementing the paper’s analysis - on the paper’s evaluation set demonstrating bug detection in the most precise configuration of our analysis as well as the precision of the analysis under different configurations.

Subject Classification

ACM Subject Classification
  • Theory of computation → Program analysis
  • Software and its engineering → Compilers
  • Software and its engineering → General programming languages
Keywords
  • Python
  • TensorFlow
  • static analysis
  • Doop
  • Wala

Metrics

  • Access Statistics
  • Total Accesses (updated on a weekly basis)
    0
    PDF Downloads

References

  1. Yuhao Zhang, Yifan Chen, Shing-Chi Cheung, Yingfei Xiong, and Lu Zhang. An empirical study on tensorflow program bugs. In Proceedings of the 27th ACM SIGSOFT International Symposium on Software Testing and Analysis, ISSTA 2018, page 129–140, New York, NY, USA, 2018. Association for Computing Machinery. URL: https://doi.org/10.1145/3213846.3213866.
Questions / Remarks / Feedback
X

Feedback for Dagstuhl Publishing


Thanks for your feedback!

Feedback submitted

Could not send message

Please try again later or send an E-mail