6 Search Results for "Hermann, Ben"

Document
DOI: 10.4230/LIPIcs.ECOOP.2024.2
Runtime Instrumentation for Reactive Components

Authors: Luca Aceto, Duncan Paul Attard, Adrian Francalanza, and Anna Ingólfsdóttir

Published in: LIPIcs, Volume 313, 38th European Conference on Object-Oriented Programming (ECOOP 2024)

Abstract
Reactive software calls for instrumentation methods that uphold the reactive attributes of systems. Runtime verification imposes another demand on the instrumentation, namely that the trace event sequences it reports to monitors are sound - that is, they reflect actual executions of the system under scrutiny. This paper presents RIARC, a novel decentralised instrumentation algorithm for outline monitors meeting these two demands. Asynchrony in reactive software complicates the instrumentation due to potential trace event loss or reordering. RIARC overcomes these challenges using a next-hop IP routing approach to rearrange and report events soundly to monitors. RIARC is validated in two ways. We subject its corresponding implementation to rigorous systematic testing to confirm its correctness. In addition, we assess this implementation via extensive empirical experiments, subjecting it to large realistic workloads to ascertain its reactiveness. Our results show that RIARC optimises its memory and scheduler usage to maintain latency feasible for soft real-time applications. We also compare RIARC to inline and centralised monitoring, revealing that it induces comparable latency to inline monitoring in moderate concurrency settings where software performs long-running, computationally-intensive tasks, such as in Big Data stream processing.
Cite as

Luca Aceto, Duncan Paul Attard, Adrian Francalanza, and Anna Ingólfsdóttir. Runtime Instrumentation for Reactive Components. In 38th European Conference on Object-Oriented Programming (ECOOP 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 313, pp. 2:1-2:33, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{aceto_et_al:LIPIcs.ECOOP.2024.2,
  author =	{Aceto, Luca and Attard, Duncan Paul and Francalanza, Adrian and Ing\'{o}lfsd\'{o}ttir, Anna},
  title =	{{Runtime Instrumentation for Reactive Components}},
  booktitle =	{38th European Conference on Object-Oriented Programming (ECOOP 2024)},
  pages =	{2:1--2:33},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-341-6},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{313},
  editor =	{Aldrich, Jonathan and Salvaneschi, Guido},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECOOP.2024.2},
  URN =		{urn:nbn:de:0030-drops-208511},
  doi =		{10.4230/LIPIcs.ECOOP.2024.2},
  annote =	{Keywords: Runtime instrumentation, decentralised monitoring, reactive systems}
}
Document
DOI: 10.4230/LIPIcs.ECOOP.2024.36
Scaling Interprocedural Static Data-Flow Analysis to Large C/C++ Applications: An Experience Report

Authors: Fabian Schiebel, Florian Sattler, Philipp Dominik Schubert, Sven Apel, and Eric Bodden

Published in: LIPIcs, Volume 313, 38th European Conference on Object-Oriented Programming (ECOOP 2024)

Abstract
Interprocedural data-flow analysis is important for computing precise information on whole programs. In theory, the popular algorithmic framework interprocedural distributive environments (IDE) provides a tool to solve distributive interprocedural data-flow problems efficiently. Yet, unfortunately, available state-of-the-art implementations of the IDE framework start to run into scalability issues for programs with several thousands of lines of code, depending on the static analysis domain. Since the IDE framework is a basic building block for many static program analyses, this presents a serious limitation. In this paper, we report on our experience with making the IDE algorithm scale to C/C++ applications with up to 500 000 lines of code. We analyze the IDE algorithm and its state-of-the-art implementations to identify their weaknesses related to scalability at both a conceptual and implementation level. Based on this analysis, we propose several optimizations to overcome these weaknesses, aiming at a sweet spot between reducing running time and memory consumption. As a result, we provide an improved IDE solver that implements our optimizations within the PhASAR static analysis framework. Our evaluation on real-world C/C++ applications shows that applying the optimizations speeds up the analysis on average by up to 7×, while also reducing memory consumption by 7× on average as well. For the first time, these optimizations allow us to analyze programs with several hundreds of thousands of lines of LLVM-IR code in reasonable time and space.
Cite as

Fabian Schiebel, Florian Sattler, Philipp Dominik Schubert, Sven Apel, and Eric Bodden. Scaling Interprocedural Static Data-Flow Analysis to Large C/C++ Applications: An Experience Report. In 38th European Conference on Object-Oriented Programming (ECOOP 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 313, pp. 36:1-36:28, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{schiebel_et_al:LIPIcs.ECOOP.2024.36,
  author =	{Schiebel, Fabian and Sattler, Florian and Schubert, Philipp Dominik and Apel, Sven and Bodden, Eric},
  title =	{{Scaling Interprocedural Static Data-Flow Analysis to Large C/C++ Applications: An Experience Report}},
  booktitle =	{38th European Conference on Object-Oriented Programming (ECOOP 2024)},
  pages =	{36:1--36:28},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-341-6},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{313},
  editor =	{Aldrich, Jonathan and Salvaneschi, Guido},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECOOP.2024.36},
  URN =		{urn:nbn:de:0030-drops-208859},
  doi =		{10.4230/LIPIcs.ECOOP.2024.36},
  annote =	{Keywords: Interprocedural data-flow analysis, IDE, LLVM, C/C++}
}
Document
DOI: 10.4230/LIPIcs.ECOOP.2024.37
Java Bytecode Normalization for Code Similarity Analysis

Authors: Stefan Schott, Serena Elisa Ponta, Wolfram Fischer, Jonas Klauke, and Eric Bodden

Published in: LIPIcs, Volume 313, 38th European Conference on Object-Oriented Programming (ECOOP 2024)

Abstract
Analyzing the similarity of two code fragments has many applications, including code clone, vulnerability and plagiarism detection. Most existing approaches for similarity analysis work on source code. However, in scenarios like plagiarism detection, copyright violation detection or Software Bill of Materials creation source code is often not available and thus similarity analysis has to be performed on binary formats. Java bytecode is a binary format executable by the Java Virtual Machine and obtained from the compilation of Java source code. Performing similarity detection on bytecode is challenging because different compilers can compile the same source code to syntactically vastly different bytecode. In this work we assess to what extent one can nonetheless enable similarity detection by bytecode normalization, a procedure to transform Java bytecode into a representation that is identical for the same original source code, irrespective of the Java compiler and Java version used during compilation. Our manual study revealed 16 classes of compilation differences that various compilation environments may induce. Based on these findings, we implemented bytecode normalization in a tool jNorm. It uses Jimple as intermediate representation, applies common code optimizations and transforms all classes of compilation difference to a normalized form, thus achieving a representation of the bytecode that is identical despite different compilation environments. Our evaluation, performed on more than 300 popular Java projects, shows that solely the act of incrementing a compiler version may cause differences in 46% of all resulting bytecode files. By applying bytecode normalization, one can remove more than 99% of these differences, thus acting as a crucial enabler for subsequent applications of bytecode similarity analysis.
Cite as

Stefan Schott, Serena Elisa Ponta, Wolfram Fischer, Jonas Klauke, and Eric Bodden. Java Bytecode Normalization for Code Similarity Analysis. In 38th European Conference on Object-Oriented Programming (ECOOP 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 313, pp. 37:1-37:29, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{schott_et_al:LIPIcs.ECOOP.2024.37,
  author =	{Schott, Stefan and Ponta, Serena Elisa and Fischer, Wolfram and Klauke, Jonas and Bodden, Eric},
  title =	{{Java Bytecode Normalization for Code Similarity Analysis}},
  booktitle =	{38th European Conference on Object-Oriented Programming (ECOOP 2024)},
  pages =	{37:1--37:29},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-341-6},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{313},
  editor =	{Aldrich, Jonathan and Salvaneschi, Guido},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECOOP.2024.37},
  URN =		{urn:nbn:de:0030-drops-208865},
  doi =		{10.4230/LIPIcs.ECOOP.2024.37},
  annote =	{Keywords: Bytecode, Java Compiler, Code Similarity Analysis}
}
Document
Track A: Algorithms, Complexity and Games
DOI: 10.4230/LIPIcs.ICALP.2024.117
Bounds on the Total Coefficient Size of Nullstellensatz Proofs of the Pigeonhole Principle

Authors: Aaron Potechin and Aaron Zhang

Published in: LIPIcs, Volume 297, 51st International Colloquium on Automata, Languages, and Programming (ICALP 2024)

Abstract
We show that the minimum total coefficient size of a Nullstellensatz proof of the pigeonhole principle on n+1 pigeons and n holes is 2^{Θ(n)}. We also investigate the ordering principle and construct an explicit Nullstellensatz proof for the ordering principle on n elements with total coefficient size 2ⁿ - n.
Cite as

Aaron Potechin and Aaron Zhang. Bounds on the Total Coefficient Size of Nullstellensatz Proofs of the Pigeonhole Principle. In 51st International Colloquium on Automata, Languages, and Programming (ICALP 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 297, pp. 117:1-117:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{potechin_et_al:LIPIcs.ICALP.2024.117,
  author =	{Potechin, Aaron and Zhang, Aaron},
  title =	{{Bounds on the Total Coefficient Size of Nullstellensatz Proofs of the Pigeonhole Principle}},
  booktitle =	{51st International Colloquium on Automata, Languages, and Programming (ICALP 2024)},
  pages =	{117:1--117:20},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-322-5},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{297},
  editor =	{Bringmann, Karl and Grohe, Martin and Puppis, Gabriele and Svensson, Ola},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICALP.2024.117},
  URN =		{urn:nbn:de:0030-drops-202604},
  doi =		{10.4230/LIPIcs.ICALP.2024.117},
  annote =	{Keywords: Proof complexity, Nullstellensatz, pigeonhole principle, coefficient size}
}
Document
Position
DOI: 10.4230/TGDK.2.1.2
Grounding Stream Reasoning Research

Authors: Pieter Bonte, Jean-Paul Calbimonte, Daniel de Leng, Daniele Dell'Aglio, Emanuele Della Valle, Thomas Eiter, Federico Giannini, Fredrik Heintz, Konstantin Schekotihin, Danh Le-Phuoc, Alessandra Mileo, Patrik Schneider, Riccardo Tommasini, Jacopo Urbani, and Giacomo Ziffer

Published in: TGDK, Volume 2, Issue 1 (2024): Special Issue on Trends in Graph Data and Knowledge - Part 2. Transactions on Graph Data and Knowledge, Volume 2, Issue 1

Abstract
In the last decade, there has been a growing interest in applying AI technologies to implement complex data analytics over data streams. To this end, researchers in various fields have been organising a yearly event called the "Stream Reasoning Workshop" to share perspectives, challenges, and experiences around this topic. In this paper, the previous organisers of the workshops and other community members provide a summary of the main research results that have been discussed during the first six editions of the event. These results can be categorised into four main research areas: The first is concerned with the technological challenges related to handling large data streams. The second area aims at adapting and extending existing semantic technologies to data streams. The third and fourth areas focus on how to implement reasoning techniques, either considering deductive or inductive techniques, to extract new and valuable knowledge from the data in the stream. This summary is written not only to provide a crystallisation of the field, but also to point out distinctive traits of the stream reasoning community. Moreover, it also provides a foundation for future research by enumerating a list of use cases and open challenges, to stimulate others to join this exciting research area.
Cite as

Pieter Bonte, Jean-Paul Calbimonte, Daniel de Leng, Daniele Dell'Aglio, Emanuele Della Valle, Thomas Eiter, Federico Giannini, Fredrik Heintz, Konstantin Schekotihin, Danh Le-Phuoc, Alessandra Mileo, Patrik Schneider, Riccardo Tommasini, Jacopo Urbani, and Giacomo Ziffer. Grounding Stream Reasoning Research. In Special Issue on Trends in Graph Data and Knowledge - Part 2. Transactions on Graph Data and Knowledge (TGDK), Volume 2, Issue 1, pp. 2:1-2:47, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@Article{bonte_et_al:TGDK.2.1.2,
  author =	{Bonte, Pieter and Calbimonte, Jean-Paul and de Leng, Daniel and Dell'Aglio, Daniele and Della Valle, Emanuele and Eiter, Thomas and Giannini, Federico and Heintz, Fredrik and Schekotihin, Konstantin and Le-Phuoc, Danh and Mileo, Alessandra and Schneider, Patrik and Tommasini, Riccardo and Urbani, Jacopo and Ziffer, Giacomo},
  title =	{{Grounding Stream Reasoning Research}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{2:1--2:47},
  ISSN =	{2942-7517},
  year =	{2024},
  volume =	{2},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.2.1.2},
  URN =		{urn:nbn:de:0030-drops-198597},
  doi =		{10.4230/TGDK.2.1.2},
  annote =	{Keywords: Stream Reasoning, Stream Processing, RDF streams, Streaming Linked Data, Continuous query processing, Temporal Logics, High-performance computing, Databases}
}
Document
DOI: 10.4230/LIPIcs.ECOOP.2021.2
Lossless, Persisted Summarization of Static Callgraph, Points-To and Data-Flow Analysis

Authors: Philipp Dominik Schubert, Ben Hermann, and Eric Bodden

Published in: LIPIcs, Volume 194, 35th European Conference on Object-Oriented Programming (ECOOP 2021)

Abstract
Static analysis is used to automatically detect bugs and security breaches, and aids compiler optimization. Whole-program analysis (WPA) can yield high precision, however causes long analysis times and thus does not match common software-development workflows, making it often impractical to use for large, real-world applications. This paper thus presents the design and implementation of ModAlyzer, a novel static-analysis approach that aims at accelerating whole-program analysis by making the analysis modular and compositional. It shows how to compute lossless, persisted summaries for callgraph, points-to and data-flow information, and it reports under which circumstances this function-level compositional analysis outperforms WPA. We implemented ModAlyzer as an extension to LLVM and PhASAR, and applied it to 12 real-world C and C++ applications. At analysis time, ModAlyzer modularly and losslessly summarizes the analysis effect of the library code those applications share, hence avoiding its repeated re-analysis. The experimental results show that the reuse of these summaries can save, on average, 72% of analysis time over WPA. Moreover, because it is lossless, the module-wise analysis fully retains precision and recall. Surprisingly, as our results show, it sometimes even yields precision superior to WPA. The initial summary generation, on average, takes about 3.67 times as long as WPA.
Cite as

Philipp Dominik Schubert, Ben Hermann, and Eric Bodden. Lossless, Persisted Summarization of Static Callgraph, Points-To and Data-Flow Analysis. In 35th European Conference on Object-Oriented Programming (ECOOP 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 194, pp. 2:1-2:31, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@InProceedings{schubert_et_al:LIPIcs.ECOOP.2021.2,
  author =	{Schubert, Philipp Dominik and Hermann, Ben and Bodden, Eric},
  title =	{{Lossless, Persisted Summarization of Static Callgraph, Points-To and Data-Flow Analysis}},
  booktitle =	{35th European Conference on Object-Oriented Programming (ECOOP 2021)},
  pages =	{2:1--2:31},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-190-0},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{194},
  editor =	{M{\o}ller, Anders and Sridharan, Manu},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECOOP.2021.2},
  URN =		{urn:nbn:de:0030-drops-140453},
  doi =		{10.4230/LIPIcs.ECOOP.2021.2},
  annote =	{Keywords: Inter-procedural static analysis, compositional analysis, LLVM, C/C++}
}
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