5 Search Results for "Ribeiro, Márcio"

Document
DOI: 10.4230/LIPIcs.ECOOP.2025.30
In-Memory Object Graph Stores

Authors: Aditya Thimmaiah, Zijian Yi, Joseph Kenis, Christopher J Rossbach, and Milos Gligoric

Published in: LIPIcs, Volume 333, 39th European Conference on Object-Oriented Programming (ECOOP 2025)

Abstract
We present a design and implementation of an in-memory object graph store, dubbed εStore. Our key innovation is a storage model - epsilon store - that equates an object on the heap to a node in a graph store. Thus any object on the heap (without changes) can be a part of one, or multiple, graph stores, and vice versa, any node in a graph store can be accessed like any other object on the heap. Specifically, each node in a graph is an object (i.e., instance of a class), and its properties and its edges are the primitive and reference fields declared in its class, respectively. Necessary classes, which are instantiated to represent nodes, are created dynamically by εStore. εStore uses a subset of the Cypher query language to query the graph store. By design, the result of any query is a table (ResultSet) of references to objects on the heap, which users can manipulate the same way as any other object on the heap in their programs. Moreover, a developer can include (transitively) an arbitrary object to become a part of a graph store. Finally, εStore introduces compile-time rewriting of Cypher queries into imperative code to improve the runtime performance. εStore can be used for a number of tasks including implementing methods for complex in-memory structures, writing complex assertions, or a stripped down version of a graph database that can conveniently be used during testing. We implement εStore in Java and show its application using the aforementioned tasks.
Cite as

Aditya Thimmaiah, Zijian Yi, Joseph Kenis, Christopher J Rossbach, and Milos Gligoric. In-Memory Object Graph Stores. In 39th European Conference on Object-Oriented Programming (ECOOP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 333, pp. 30:1-30:30, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{thimmaiah_et_al:LIPIcs.ECOOP.2025.30,
  author =	{Thimmaiah, Aditya and Yi, Zijian and Kenis, Joseph and Rossbach, Christopher J and Gligoric, Milos},
  title =	{{In-Memory Object Graph Stores}},
  booktitle =	{39th European Conference on Object-Oriented Programming (ECOOP 2025)},
  pages =	{30:1--30:30},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-373-7},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{333},
  editor =	{Aldrich, Jonathan and Silva, Alexandra},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECOOP.2025.30},
  URN =		{urn:nbn:de:0030-drops-233225},
  doi =		{10.4230/LIPIcs.ECOOP.2025.30},
  annote =	{Keywords: Object stores, Graph stores, Cypher}
}
Document
Replication Paper
DOI: 10.4230/LIPIcs.ECOOP.2025.40
Scaling Up: Revisiting Mining Android Sandboxes at Scale for Malware Classification (Replication Paper)

Authors: Francisco Handrick Tomaz da Costa, Ismael Medeiros, Leandro Oliveira, João Calássio, Rodrigo Bonifácio, Krishna Narasimhan, Mira Mezini, and Márcio Ribeiro

Published in: LIPIcs, Volume 333, 39th European Conference on Object-Oriented Programming (ECOOP 2025)

Abstract
The widespread use of smartphones in daily life has raised concerns about privacy and security among researchers and practitioners. Privacy issues are generally highly prevalent in mobile applications, particularly targeting the Android platform - the most popular mobile operating system. For this reason, several techniques have been proposed to identify malicious behavior in Android applications, including the Mining Android Sandbox approach (MAS approach), which aims to identify malicious behavior in repackaged Android applications (apps). However, previous empirical studies evaluated the MAS approach using a small dataset consisting of only 102 pairs of original and repackaged apps. This limitation raises questions about the external validity of their findings and whether the MAS approach can be generalized to larger datasets. To address these concerns, this paper presents the results of a replication study focused on evaluating the performance of the MAS approach regarding its capabilities of correctly classifying malware from different families. Unlike previous studies, our research employs a dataset that is an order of magnitude larger, comprising 4,076 pairs of apps covering a more diverse range of Android malware families. Surprisingly, our findings indicate a poor performance of the MAS approach for identifying malware, with the F1-score decreasing from 0.90 for the small dataset used in the previous studies to 0.54 in our more extensive dataset. Upon closer examination, we discovered that certain malware families partially account for the low accuracy of the MAS approach, which fails to classify a repackaged version of an app as malware correctly. Our findings highlight the limitations of the MAS approach, particularly when scaled, and underscore the importance of complementing it with other techniques to detect a broader range of malware effectively. This opens avenues for further discussion on addressing the blind spots that affect the accuracy of the MAS approach.
Cite as

Francisco Handrick Tomaz da Costa, Ismael Medeiros, Leandro Oliveira, João Calássio, Rodrigo Bonifácio, Krishna Narasimhan, Mira Mezini, and Márcio Ribeiro. Scaling Up: Revisiting Mining Android Sandboxes at Scale for Malware Classification (Replication Paper). In 39th European Conference on Object-Oriented Programming (ECOOP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 333, pp. 40:1-40:26, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{handricktomazdacosta_et_al:LIPIcs.ECOOP.2025.40,
  author =	{Handrick Tomaz da Costa, Francisco and Medeiros, Ismael and Oliveira, Leandro and Cal\'{a}ssio, Jo\~{a}o and Bonif\'{a}cio, Rodrigo and Narasimhan, Krishna and Mezini, Mira and Ribeiro, M\'{a}rcio},
  title =	{{Scaling Up: Revisiting Mining Android Sandboxes at Scale for Malware Classification}},
  booktitle =	{39th European Conference on Object-Oriented Programming (ECOOP 2025)},
  pages =	{40:1--40:26},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-373-7},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{333},
  editor =	{Aldrich, Jonathan and Silva, Alexandra},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECOOP.2025.40},
  URN =		{urn:nbn:de:0030-drops-233320},
  doi =		{10.4230/LIPIcs.ECOOP.2025.40},
  annote =	{Keywords: Android Malware Detection, Dynamic Analysis, Mining Android Sandboxes}
}
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/DARTS.1.1.7
The Love/Hate Relationship with the C Preprocessor: An Interview Study (Artifact)

Authors: Flávio Medeiros, Christian Kästner, Márcio Ribeiro, Sarah Nadi, and Rohit Gheyi

Published in: DARTS, Volume 1, Issue 1, Special Issue of the 29th European Conference on Object-Oriented Programming (ECOOP 2015)

Abstract
This appendix presents detailed information about the research methods we used in the study, subject characterization, grounded theory process that we followed strictly, and the survey we performed in the study. It provides helpful data for understanding the subtler points of the companion paper and for reproducibility.
Cite as

Flávio Medeiros, Christian Kästner, Márcio Ribeiro, Sarah Nadi, and Rohit Gheyi. The Love/Hate Relationship with the C Preprocessor: An Interview Study (Artifact). In Special Issue of the 29th European Conference on Object-Oriented Programming (ECOOP 2015). Dagstuhl Artifacts Series (DARTS), Volume 1, Issue 1, pp. 7:1-7:32, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2015)

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@Article{medeiros_et_al:DARTS.1.1.7,
  author =	{Medeiros, Fl\'{a}vio and K\"{a}stner, Christian and Ribeiro, M\'{a}rcio and Nadi, Sarah and Gheyi, Rohit},
  title =	{{The Love/Hate Relationship with the C Preprocessor: An Interview Study (Artifact)}},
  pages =	{7:1--7:32},
  journal =	{Dagstuhl Artifacts Series},
  ISSN =	{2509-8195},
  year =	{2015},
  volume =	{1},
  number =	{1},
  editor =	{Medeiros, Fl\'{a}vio and K\"{a}stner, Christian and Ribeiro, M\'{a}rcio and Nadi, Sarah and Gheyi, Rohit},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DARTS.1.1.7},
  URN =		{urn:nbn:de:0030-drops-55162},
  doi =		{10.4230/DARTS.1.1.7},
  annote =	{Keywords: C Preprocessor, CPP, Interviews, Surveys, and Grounded Theory}
}
Document
DOI: 10.4230/LIPIcs.ECOOP.2015.495
The Love/Hate Relationship with the C Preprocessor: An Interview Study

Authors: Flávio Medeiros, Christian Kästner, Márcio Ribeiro, Sarah Nadi, and Rohit Gheyi

Published in: LIPIcs, Volume 37, 29th European Conference on Object-Oriented Programming (ECOOP 2015)

Abstract
The C preprocessor has received strong criticism in academia, among others regarding separation of concerns, error proneness, and code obfuscation, but is widely used in practice. Many (mostly academic) alternatives to the preprocessor exist, but have not been adopted in practice. Since developers continue to use the preprocessor despite all criticism and research, we ask how practitioners perceive the C preprocessor. We performed interviews with 40 developers, used grounded theory to analyze the data, and cross-validated the results with data from a survey among 202 developers, repository mining, and results from previous studies. In particular, we investigated four research questions related to why the preprocessor is still widely used in practice, common problems, alternatives, and the impact of undisciplined annotations. Our study shows that developers are aware of the criticism the C preprocessor receives, but use it nonetheless, mainly for portability and variability. Many developers indicate that they regularly face preprocessor-related problems and preprocessor-related bugs. The majority of our interviewees do not see any current C-native technologies that can entirely replace the C preprocessor. However, developers tend to mitigate problems with guidelines, even though those guidelines are not enforced consistently. We report the key insights gained from our study and discuss implications for practitioners and researchers on how to better use the C preprocessor to minimize its negative impact.
Cite as

Flávio Medeiros, Christian Kästner, Márcio Ribeiro, Sarah Nadi, and Rohit Gheyi. The Love/Hate Relationship with the C Preprocessor: An Interview Study. In 29th European Conference on Object-Oriented Programming (ECOOP 2015). Leibniz International Proceedings in Informatics (LIPIcs), Volume 37, pp. 495-518, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2015)

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@InProceedings{medeiros_et_al:LIPIcs.ECOOP.2015.495,
  author =	{Medeiros, Fl\'{a}vio and K\"{a}stner, Christian and Ribeiro, M\'{a}rcio and Nadi, Sarah and Gheyi, Rohit},
  title =	{{The Love/Hate Relationship with the C Preprocessor: An Interview Study}},
  booktitle =	{29th European Conference on Object-Oriented Programming (ECOOP 2015)},
  pages =	{495--518},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-939897-86-6},
  ISSN =	{1868-8969},
  year =	{2015},
  volume =	{37},
  editor =	{Boyland, John Tang},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECOOP.2015.495},
  URN =		{urn:nbn:de:0030-drops-52350},
  doi =		{10.4230/LIPIcs.ECOOP.2015.495},
  annote =	{Keywords: C Preprocessor, CPP, Interviews, Surveys, and Grounded Theory}
}
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