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Automated Large-Scale Multi-Language Dynamic Program Analysis in the Wild (Artifact)

Authors Alex Villazón , Haiyang Sun, Andrea Rosà, Eduardo Rosales , Daniele Bonetta, Isabella Defilippis, Sergio Oporto, Walter Binder

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DARTS.5.2.11.pdf
  • Filesize: 343 kB
  • 3 pages

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Subject Classification

ACM Subject Classification
  • Software and its engineering → Dynamic analysis
Keywords
  • Dynamic program analysis
  • code repositories
  • GitHub
  • Node.js
  • Java
  • Scala
  • promises
  • JIT-unfriendly code
  • task granularity

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Abstract

This artifact provides a preliminary release of NAB, a distributed infrastructure for executing large-scale dynamic program analyses (DPAs). The artifact consists of ready-to-use Docker containers that allow one to run different DPA tools (Deep-Promise, JITProf, and tgp) on Node.js, Java, and Scala projects hosted on GitHub. The artifact enables the reproduction of the figures and tables of the related paper "Automated Large-scale Multi-language Dynamic Program Analysis in the Wild" with pre-collected data (several GBs) and the execution of DPAs on specific sets of GitHub projects.

Cite As Get BibTex

Alex Villazón, Haiyang Sun, Andrea Rosà, Eduardo Rosales, Daniele Bonetta, Isabella Defilippis, Sergio Oporto, and Walter Binder. Automated Large-Scale Multi-Language Dynamic Program Analysis in the Wild (Artifact). In Special Issue of the 33rd European Conference on Object-Oriented Programming (ECOOP 2019). Dagstuhl Artifacts Series (DARTS), Volume 5, Issue 2, pp. 11:1-11:3, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019) https://doi.org/10.4230/DARTS.5.2.11

Author Details

Alex Villazón
  • Universidad Privada Boliviana, Bolivia
Haiyang Sun
  • Università della Svizzera italiana, Switzerland
Andrea Rosà
  • Università della Svizzera italiana, Switzerland
Eduardo Rosales
  • Università della Svizzera italiana, Switzerland
Daniele Bonetta
  • Oracle Labs, United States
Isabella Defilippis
  • Universidad Privada Boliviana, Bolivia
Sergio Oporto
  • Universidad Privada Boliviana, Bolivia
Walter Binder
  • Università della Svizzera italiana, Switzerland

Acknowledgements

This work has been supported by Oracle (ERO project 1332), Swiss National Science Foundation (scientific exchange project IZSEZ0_177215), Hasler Foundation (project 18012), and by a Bridging Grant with Japan (BG 04-122017).

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  MD5 Sum: fa2151a3fa429d676e7eb2c77d5aad62 (Get MD5 Sum)

Related Article

  • Alex Villazón, Haiyang Sun, Andrea Rosà, Eduardo Rosales, Daniele Bonetta, Isabella Defilippis, Sergio Oporto, and Walter Binder, "Automated Large-Scale Multi-Language Dynamic Program Analysis in the Wild", in 33rd European Conference on Object-Oriented Programming (ECOOP 2019), LIPIcs, Vol. 134, pp. 20:1 - 20:27, 2019. https://dx.doi.org/10.4230/LIPIcs.ECOOP.2019.20

References

  1. Oracle Corporation. Java SE HotSpot at a Glance. https://www.oracle.com/technetwork/java/javase/tech/index-jsp-136373.html, 2018.
  2. L. Gong, M. Pradel, and K. Sen. JITProf: Pinpointing JIT-unfriendly JavaScript Code. In ESEC/FSE, pages 357-368, 2015. Google Scholar
  3. A. Rosà, E. Rosales, and W. Binder. Analyzing and Optimizing Task Granularity on the JVM. In CGO, pages 27-37, 2018. Google Scholar
  4. A. Rosà, E. Rosales, and W. Binder. Analysis and Optimization of Task Granularity on the Java Virtual Machine. ACM Transactions on Programming Languages and Systems (TOPLAS), pages 1-47, 2019. Google Scholar
  5. E. Rosales, A. Rosà, and W. Binder. tgp: a Task-Granularity Profiler for the Java Virtual Machine. In APSEC, pages 570-575, 2017. Google Scholar
  6. A. Villazón, H. Sun, A. Rosà, E. Rosales, D. Bonetta, I. Defilippis, S. Oporto, and W. Binder. Automated Large-scale Multi-language Dynamic Program Analysis in the Wild. In ECOOP, London, UK, July 2019. Google Scholar
  7. T. Würthinger, C. Wimmer, C. Humer, A. Wöß, L. Stadler, C. Seaton, G. Duboscq, D. Simon, and M. Grimmer. Practical Partial Evaluation for High-performance Dynamic Language Runtimes. In PLDI, pages 662-676, 2017. Google Scholar
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