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Documents authored by Bonetta, Daniele

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)

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@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)

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@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}
}
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