Search Results

Documents authored by Binder, Walter

Document
Artifact
DOI: 10.4230/DARTS.5.2.11
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, and Walter Binder

Published in: DARTS, Volume 5, Issue 2, Special Issue of the 33rd European Conference on Object-Oriented Programming (ECOOP 2019)

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

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)

Copy BibTex To Clipboard

@Article{villazon_et_al:DARTS.5.2.11,
  author =	{Villaz\'{o}n, Alex and Sun, Haiyang and Ros\`{a}, Andrea and Rosales, Eduardo and Bonetta, Daniele and Defilippis, Isabella and Oporto, Sergio and Binder, Walter},
  title =	{{Automated Large-Scale Multi-Language Dynamic Program Analysis in the Wild}},
  pages =	{11:1--11:3},
  journal =	{Dagstuhl Artifacts Series},
  ISSN =	{2509-8195},
  year =	{2019},
  volume =	{5},
  number =	{2},
  editor =	{Villaz\'{o}n, Alex and Sun, Haiyang and Ros\`{a}, Andrea and Rosales, Eduardo and Bonetta, Daniele and Defilippis, Isabella and Oporto, Sergio and Binder, Walter},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DARTS.5.2.11},
  URN =		{urn:nbn:de:0030-drops-107881},
  doi =		{10.4230/DARTS.5.2.11},
  annote =	{Keywords: Dynamic program analysis, code repositories, GitHub, Node.js, Java, Scala, promises, JIT-unfriendly code, task granularity}
}
Document
Tool Insights Paper
DOI: 10.4230/LIPIcs.ECOOP.2019.20
Automated Large-Scale Multi-Language Dynamic Program Analysis in the Wild (Tool Insights Paper)

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

Published in: LIPIcs, Volume 134, 33rd European Conference on Object-Oriented Programming (ECOOP 2019)

Abstract
Today’s availability of open-source software is overwhelming, and the number of free, ready-to-use software components in package repositories such as NPM, Maven, or SBT is growing exponentially. In this paper we address two straightforward yet important research questions: would it be possible to develop a tool to automate dynamic program analysis on public open-source software at a large scale? Moreover, and perhaps more importantly, would such a tool be useful? We answer the first question by introducing NAB, a tool to execute large-scale dynamic program analysis of open-source software in the wild. NAB is fully-automatic, language-agnostic, and can scale dynamic program analyses on open-source software up to thousands of projects hosted in code repositories. Using NAB, we analyzed more than 56K Node.js, Java, and Scala projects. Using the data collected by NAB we were able to (1) study the adoption of new language constructs such as JavaScript Promises, (2) collect statistics about bad coding practices in JavaScript, and (3) identify Java and Scala task-parallel workloads suitable for inclusion in a domain-specific benchmark suite. We consider such findings and the collected data an affirmative answer to the second question.
Cite as

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 (Tool Insights Paper). In 33rd European Conference on Object-Oriented Programming (ECOOP 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 134, pp. 20:1-20:27, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

Copy BibTex To Clipboard

@InProceedings{villazon_et_al:LIPIcs.ECOOP.2019.20,
  author =	{Villaz\'{o}n, Alex and Sun, Haiyang and Ros\`{a}, Andrea and Rosales, Eduardo and Bonetta, Daniele and Defilippis, Isabella and Oporto, Sergio and Binder, Walter},
  title =	{{Automated Large-Scale Multi-Language Dynamic Program Analysis in the Wild}},
  booktitle =	{33rd European Conference on Object-Oriented Programming (ECOOP 2019)},
  pages =	{20:1--20:27},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-111-5},
  ISSN =	{1868-8969},
  year =	{2019},
  volume =	{134},
  editor =	{Donaldson, Alastair F.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECOOP.2019.20},
  URN =		{urn:nbn:de:0030-drops-108127},
  doi =		{10.4230/LIPIcs.ECOOP.2019.20},
  annote =	{Keywords: Dynamic program analysis, code repositories, GitHub, Node.js, Java, Scala, promises, JIT-unfriendly code, task granularity}
}
Document
DOI: 10.4230/LIPIcs.ECOOP.2017.30
An Empirical Study on Deoptimization in the Graal Compiler

Authors: Yudi Zheng, Lubomír Bulej, and Walter Binder

Published in: LIPIcs, Volume 74, 31st European Conference on Object-Oriented Programming (ECOOP 2017)

Abstract
Managed language platforms such as the Java Virtual Machine or the Common Language Runtime rely on a dynamic compiler to achieve high performance. Besides making optimization decisions based on the actual program execution and the underlying hardware platform, a dynamic compiler is also in an ideal position to perform speculative optimizations. However, these tend to increase the compilation costs, because unsuccessful speculations trigger deoptimization and recompilation of the affected parts of the program, wasting previous work. Even though speculative optimizations are widely used, the costs of these optimizations in terms of extra compilation work has not been previously studied. In this paper, we analyze the behavior of the Graal dynamic compiler integrated in Oracle's HotSpot Virtual Machine. We focus on situations which cause program execution to switch from machine code to the interpreter, and compare application performance using three different deoptimization strategies which influence the amount of extra compilation work done by Graal. Using an adaptive deoptimization strategy, we managed to improve the average start-up performance of benchmarks from the DaCapo, ScalaBench, and Octane benchmark suites, mostly by avoiding wasted compilation work. On a single-core system, we observed an average speed-up of 6.4% for the DaCapo and ScalaBench workloads, and a speed-up of 5.1% for the Octane workloads; the improvement decreases with an increasing number of available CPU cores. We also find that the choice of a deoptimization strategy has negligible impact on steady-state performance. This indicates that the cost of speculation matters mainly during start-up, where it can disturb the delicate balance between executing the program and the compiler, but is quickly amortized in steady state.
Cite as

Yudi Zheng, Lubomír Bulej, and Walter Binder. An Empirical Study on Deoptimization in the Graal Compiler. In 31st European Conference on Object-Oriented Programming (ECOOP 2017). Leibniz International Proceedings in Informatics (LIPIcs), Volume 74, pp. 30:1-30:30, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)

Copy BibTex To Clipboard

@InProceedings{zheng_et_al:LIPIcs.ECOOP.2017.30,
  author =	{Zheng, Yudi and Bulej, Lubom{\'\i}r and Binder, Walter},
  title =	{{An Empirical Study on Deoptimization in the Graal Compiler}},
  booktitle =	{31st European Conference on Object-Oriented Programming (ECOOP 2017)},
  pages =	{30:1--30:30},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-035-4},
  ISSN =	{1868-8969},
  year =	{2017},
  volume =	{74},
  editor =	{M\"{u}ller, Peter},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECOOP.2017.30},
  URN =		{urn:nbn:de:0030-drops-72583},
  doi =		{10.4230/LIPIcs.ECOOP.2017.30},
  annote =	{Keywords: dynamic compiler, profile-guided optimization, deoptimization}
}
Any Issues?
X

Feedback on the Current Page

CAPTCHA

Thanks for your feedback!

Feedback submitted to Dagstuhl Publishing

Could not send message

Please try again later or send an E-mail
© 2023-2025 Schloss Dagstuhl – LZI GmbH About DROPS Imprint Privacy Contact