Vincent Lemaire

167 papers A* 3B 26C 2Journal 51Unranked 63
YearRankTypeTitle / Venue / Authors
2026 ed.
AALTD@ECML/PKDD
Vincent Lemaire, Georgiana Ifrim, Anthony J. Bagnall, Simon Malinowski, Patrick Schäfer, Romain Tavenard
2026 J jnl
CoRR
Aurélien Renault, Alexis Bondu, Antoine Cornuéjols, Vincent Lemaire
2026 J jnl
CoRR
Vincent Lemaire, Nédra Meloulli, Pierre Jaquet
2025 ed.
AALTD@ECML/PKDD
Vincent Lemaire, Georgiana Ifrim, Anthony J. Bagnall, Thomas Guyet, Simon Malinowski, Patrick Schäfer, Romain Tavenard
2025 conf
EGC
Hugo Peuzet, Pascale Kuntz, Frank Meyer, Vincent Lemaire, Killian Le Mau
2025 B conf
DSAA
Aurélien Renault, Dominique Gay, Noureddine Yassine Nair Benrekia, Vincent Lemaire, Alexis Bondu
2025 conf
EGC
Ilies Chibane, Thomas George, Pierre Nodet, Vincent Lemaire
2025 J jnl
CoRR
Ilies Chibane, Thomas George, Pierre Nodet, Vincent Lemaire
2025 conf
EGC
Marine Hamon, Vincent Lemaire, Noureddine Yassine Nair Benrekia, Samuel Berlemont, Julien Cumin
2025 conf
EGC
Arthur Hoarau, Vincent Lemaire
2025 J jnl
CoRR
Aurélien Renault, Alexis Bondu, Antoine Cornuéjols, Vincent Lemaire
2025 J jnl
Trans. Mach. Learn. Res.
Aurélien Renault, Alexis Bondu, Antoine Cornuéjols, Vincent Lemaire
2025 J jnl
SIGKDD Explor.
Ludovic Arga, François Bélorgey, Arnaud Braud, Romain Carbou, Nathalie Charbonniaud, Catherine Colomes, Lionel Delphin-Poulat, David Excoffier, Christel Fauché, Thomas George, Frédéric Guyard, Thomas Hassan, Quentin Lampin, Vincent Lemaire, Pierre Nodet, Pawel Piotrowski, Krzysztof Sapiejewski, Emilie Sirvent-Hien, Tamara Tosic
2025 J jnl
CoRR
Marc Boullé, Nicolas Voisine, Bruno Guerraz, Carine Hue, Felipe Olmos, Vladimir Popescu, Stéphane Gouache, Stéphane Bouget, Alexis Bondu, Luc-Aurélien Gauthier, Noureddine Yacine Nair Benrekia, Fabrice Clérot, Vincent Lemaire
2025 conf
EGC
Marc Boullé, Nicolas Voisine, Bruno Guerraz, Carine Hue, Felipe Olmos, Vladimir Popescu, Stéphane Gouache, Stéphane Bouget, Alexis Bondu, Luc-Aurélien Gauthier, Noureddine Yassine Nair Benrekia, Fabrice Clérot, Vincent Lemaire
2025 conf
IDEAL (2)
Xihui Wang, Hugo Peuzet, Pascale Kuntz, Frank Meyer, Vincent Lemaire
2025 B conf
DSAA
Hugo Peuzet, Pascale Kuntz, Frank Meyer, Vincent Lemaire, Killian Le Mau
2025 J jnl
CoRR
Marine Hamon, Vincent Lemaire, Noureddine Yassine Nair Benrekia, Samuel Berlemont, Julien Cumin
2025 conf
AALTD@ECML/PKDD
Marine Hamon, Vincent Lemaire, Noureddine Yassine Nair Benrekia, Samuel Berlemont, Julien Cumin
2024 J jnl
Data Min. Knowl. Discov.
Colin Troisemaine, Alexandre Reiffers-Masson, Stéphane Gosselin, Vincent Lemaire, Sandrine Vaton
2024 B conf
IEEE Big Data
Oumaima Badi, Maxime Devanne, Ali Ismail-Fawaz, Javidan Abdullayev, Vincent Lemaire, Stefano Berretti, Jonathan Weber, Germain Forestier
2024 J jnl
CoRR
Colin Troisemaine, Vincent Lemaire
2024 J jnl
CoRR
Arthur Hoarau, Vincent Lemaire
2024 J jnl
CoRR
Aurélien Renault, Alexis Bondu, Antoine Cornuéjols, Vincent Lemaire
2024 J jnl
Mach. Learn.
Arthur Hoarau, Vincent Lemaire, Yolande Le Gall, Jean-Christophe Dubois, Arnaud Martin
2024 J jnl
CoRR
Thomas George, Pierre Nodet, Alexis Bondu, Vincent Lemaire
2024 J jnl
Trans. Mach. Learn. Res.
Thomas George, Pierre Nodet, Alexis Bondu, Vincent Lemaire
2024 conf
EGC
Arthur Hoarau, Vincent Lemaire, Arnaud Martin, Jean-Christophe Dubois, Yolande Le Gall
2024 ed.
IAL@PKDD/ECML
Mirko Bunse, Marek Herde, Georg Krempl, Vincent Lemaire, Alaa Tharwat, Minh Tuan Pham, Amal Saadallah
2024 B conf
IJCNN
Vincent Lemaire, Nathan Le Boudec, Victor Guyomard, Françoise Fessant
2024 conf
EGC
Vincent Lemaire, Nathan Le Boudec, Françoise Fessant, Victor Guyomard
2024 J jnl
CoRR
Aurélien Renault, Youssef Achenchabe, Edouard Bertrand, Alexis Bondu, Antoine Cornuéjols, Vincent Lemaire, Asma Dachraoui
2023 J jnl
CoRR
Colin Troisemaine, Alexandre Reiffers-Masson, Stéphane Gosselin, Vincent Lemaire, Sandrine Vaton
2023 ed.
AALTD@ECML/PKDD
Thomas Guyet, Georgiana Ifrim, Simon Malinowski, Anthony J. Bagnall, Patrick Schäfer, Vincent Lemaire
2023 ed.
AALTD@ECML/PKDD
Georgiana Ifrim, Romain Tavenard, Anthony J. Bagnall, Patrick Schäfer, Simon Malinowski, Thomas Guyet, Vincent Lemaire
2023 conf
PKDD/ECML Workshops (1)
Vincent Lemaire, Fabrice Clérot, Marc Boullé
2023 J jnl
CoRR
Vincent Lemaire, Fabrice Clérot, Marc Boullé
2023 conf
ECML/PKDD (7)
Colin Troisemaine, Joachim Flocon-Cholet, Stéphane Gosselin, Alexandre Reiffers-Masson, Sandrine Vaton, Vincent Lemaire
2023 J jnl
CoRR
Colin Troisemaine, Joachim Flocon-Cholet, Stéphane Gosselin, Alexandre Reiffers-Masson, Sandrine Vaton, Vincent Lemaire
2023 B conf
IJCNN
Aurélien Renault, Alexis Bondu, Vincent Lemaire, Dominique Gay
2023 J jnl
CoRR
Aurélien Renault, Alexis Bondu, Vincent Lemaire, Dominique Gay
2023 J jnl
CoRR
Pierre Nodet, Vincent Lemaire, Alexis Bondu, Antoine Cornuéjols
2023 J jnl
Mach. Learn.
Pierre Nodet, Vincent Lemaire, Alexis Bondu, Antoine Cornuéjols
2023 conf
EGC
Vincent Lemaire, Fabrice Clérot, Marc Boullé
2023 conf
EGC
Colin Troisemaine, Joachim Flocon-Cholet, Stéphane Gosselin, Sandrine Vaton, Alexandre Reiffers-Masson, Vincent Lemaire
2023 J jnl
CoRR
Arthur Hoarau, Vincent Lemaire, Arnaud Martin, Jean-Christophe Dubois, Yolande Le Gall
2023 conf
AALTD@ECML/PKDD
Arik Ermshaus, Patrick Schäfer, Anthony J. Bagnall, Thomas Guyet, Georgiana Ifrim, Vincent Lemaire, Ulf Leser, Colin Leverger, Simon Malinowski
2023 J jnl
CoRR
Colin Troisemaine, Vincent Lemaire, Stéphane Gosselin, Alexandre Reiffers-Masson, Joachim Flocon-Cholet, Sandrine Vaton
2023 ed.
IAL@PKDD/ECML
Mirko Bunse, Barbara Hammer, Georg Krempl, Vincent Lemaire, Alaa Tharwat, Amal Saadallah
2023 J jnl
CoRR
Vincent Lemaire, Nathan Le Boudec, Françoise Fessant, Victor Guyomard
2023 J jnl
CoRR
Pierre Nodet, Vincent Lemaire, Alexis Bondu, Antoine Cornuéjols
2022 conf
ICKG
Colin Troisemaine, Joachim Flocon-Cholet, Stéphane Gosselin, Sandrine Vaton, Alexandre Reiffers-Masson, Vincent Lemaire
2022 J jnl
CoRR
Colin Troisemaine, Joachim Flocon-Cholet, Stéphane Gosselin, Sandrine Vaton, Alexandre Reiffers-Masson, Vincent Lemaire
2022 conf
EGC
Colin Troisemaine, Vincent Lemaire
2022 J jnl
CoRR
Colin Troisemaine, Joachim Flocon-Cholet, Stéphane Gosselin, Sandrine Vaton, Alexandre Reiffers-Masson, Vincent Lemaire
2022 J jnl
CoRR
Youssef Achenchabe, Alexis Bondu, Antoine Cornuéjols, Vincent Lemaire
2022 B conf
IJCNN
Youssef Achenchabe, Alexis Bondu, Antoine Cornuéjols, Vincent Lemaire
2022 J jnl
CoRR
Alexis Bondu, Youssef Achenchabe, Albert Bifet, Fabrice Clérot, Antoine Cornuéjols, João Gama, Georges Hébrail, Vincent Lemaire, Pierre-François Marteau
2022 J jnl
SIGKDD Explor.
Alexis Bondu, Youssef Achenchabe, Albert Bifet, Fabrice Clérot, Antoine Cornuéjols, João Gama, Georges Hébrail, Vincent Lemaire, Pierre-Francois Marteau
2022 ed.
IAL@PKDD/ECML
Georg Krempl, Vincent Lemaire, Daniel Kottke, Andreas Holzinger, Barbara Hammer
2022 B conf
IEEE Big Data
Laura Uhl, Vincent Augusto, Vincent Lemaire, Youenn Alexandre, Fanny Jardinaud, Paolo Bercelli, Saber Aloui
2022 conf
EGC
Pierre Nodet, Vincent Lemaire, Alexis Bondu, Antoine Cornuéjols
2022 C conf
ACML
Youssef Achenchabe, Alexis Bondu, Antoine Cornuéjols, Vincent Lemaire
2021 ed.
AALTD@ECML/PKDD
Vincent Lemaire, Simon Malinowski, Anthony J. Bagnall, Thomas Guyet, Romain Tavenard, Georgiana Ifrim
2021 J jnl
CoRR
Colin Troisemaine, Vincent Lemaire
2021 conf
IAL@PKDD/ECML
Pierre Nodet, Vincent Lemaire, Alexis Bondu, Antoine Cornuéjols
2021 J jnl
CoRR
Pierre Nodet, Vincent Lemaire, Alexis Bondu, Antoine Cornuéjols
2021 J jnl
CoRR
Youssef Achenchabe, Alexis Bondu, Antoine Cornuéjols, Vincent Lemaire
2021 B conf
DSAA
Paul-Emile Zafar, Youssef Achenchabe, Alexis Bondu, Antoine Cornuéjols, Vincent Lemaire
2021 J jnl
CoRR
Youssef Achenchabe, Alexis Bondu, Antoine Cornuéjols, Vincent Lemaire
2021 conf
IAL@PKDD/ECML
Daniel Zhu, Arnaud Martin, Yolande Le Gall, Jean-Christophe Dubois, Vincent Lemaire
2021 ed.
EGC
Jérôme Azé, Vincent Lemaire
2021 B conf
IJCNN
Pierre Nodet, Vincent Lemaire, Alexis Bondu, Antoine Cornuéjols, Adam Ouorou
2021 B conf
IJCNN
Pierre Nodet, Vincent Lemaire, Alexis Bondu, Antoine Cornuéjols, Adam Ouorou
2021 conf
PAKDD (1)
Dominique Gay, Alexis Bondu, Vincent Lemaire, Marc Boullé
2021 J jnl
CoRR
Dominique Gay, Alexis Bondu, Vincent Lemaire, Marc Boullé
2021 conf
ICDM (Workshops)
Xihui Wang, Pascale Kuntz, Frank Meyer, Vincent Lemaire
2020 ed.
AALTD@PKDD/ECML
Vincent Lemaire, Simon Malinowski, Anthony J. Bagnall, Alexis Bondu, Thomas Guyet, Romain Tavenard
2020 ed.
AALTD@PKDD/ECML
Vincent Lemaire, Simon Malinowski, Anthony J. Bagnall, Thomas Guyet, Romain Tavenard, Georgiana Ifrim
2020 conf
EGC
Louis Desreumaux, Vincent Lemaire
2020 J jnl
CoRR
Pierre Nodet, Vincent Lemaire, Alexis Bondu, Antoine Cornuéjols, Adam Ouorou
2020 J jnl
CoRR
Pierre Nodet, Vincent Lemaire, Alexis Bondu, Antoine Cornuéjols
2020 conf
IAL@PKDD/ECML
Louis Desreumaux, Vincent Lemaire
2020 J jnl
CoRR
Louis Desreumaux, Vincent Lemaire
2020 B conf
DaWaK
Dominique Gay, Alexis Bondu, Vincent Lemaire, Marc Boullé, Fabrice Clérot
2020 J jnl
CoRR
Hugo Le Baher, Vincent Lemaire, Romain Trinquart
2020 J jnl
CoRR
Vincent Lemaire, Oumaima Alaoui Ismaili, Antoine Cornuéjols, Dominique Gay
2020 ed.
IAL@PKDD/ECML
Daniel Kottke, Georg Krempl, Vincent Lemaire, Andreas Holzinger, Adrian Calma
2020 conf
EGC
Alexis Bondu, Dominique Gay, Vincent Lemaire, Marc Boullé, Eole Cervenka
2019 conf
EGC
Sébastien Godard, Nicolas Voisine, Tanguy Urvoy, Vincent Lemaire
2019 C conf
ACML
Alexis Bondu, Dominique Gay, Vincent Lemaire, Marc Boullé, Eole Cervenka
2019 B conf
SIGdial
Jean Léon Bouraoui, Sonia Le Meitour, Romain Carbou, Lina Maria Rojas-Barahona, Vincent Lemaire
2019 conf
AALTD@PKDD/ECML
Vincent Lemaire, Fabien Boitier, Jelena Pesic, Alexis Bondu, Stéphane Ragot, Fabrice Clérot
2019 J jnl
CoRR
Dominique Gay, Vincent Lemaire
2019 conf
IDEAL (1)
Colin Leverger, Simon Malinowski, Thomas Guyet, Vincent Lemaire, Alexis Bondu, Alexandre Termier
2018 conf
EGC
Vincent Lemaire, Oumaima Alaoui Ismaili
2018 J jnl
CoRR
Colin Leverger, Vincent Lemaire, Simon Malinowski, Thomas Guyet, Laurence Rozé
2018 conf
EGC
Colin Leverger, Régis Marguerie, Vincent Lemaire, Thomas Guyet, Simon Malinowski
2018 ed.
IAL@PKDD/ECML
Georg Krempl, Vincent Lemaire, Daniel Kottke, Adrian Calma, Andreas Holzinger, Robi Polikar, Bernhard Sick
2018 conf
ECOC
Fabien Boitier, Jelena Pesic, Vincent Lemaire, Eric Dutisseuil, José Manuel Estarán Tolosa, Philippe Jennevé, Nicolas Le Moing, Haïk Mardoyan, Patricia Layec
2017 conf
ECOC
Fabien Boitier, Vincent Lemaire, Jelena Pesic, Lucia Chavarría, Patricia Layec, Sébastien Bigo, Eric Dutisseuil
2017 ed.
IAL@PKDD/ECML
Georg Krempl, Vincent Lemaire, Robi Polikar, Bernhard Sick, Daniel Kottke, Adrian Calma
2017 conf
EGC
Oumaima Alaoui Ismaili, Vincent Lemaire, Antoine Cornuéjols
2016 conf
EGC
Bruno Guerraz, Marc Boullé, Dominique Gay, Vincent Lemaire, Fabrice Clérot
2016 conf
ICDM Workshops
Pierre-Xavier Loeffel, Vincent Lemaire, Christophe Marsala, Marcin Detyniecki
2016 ed.
AL@iKNOW
Georg Krempl, Vincent Lemaire, Edwin Lughofer, Daniel Kottke
2016 conf
EGC
Oumaima Alaoui Ismaili, Vincent Lemaire, Antoine Cornuéjols
2015 B conf
IJCNN
Vincent Lemaire, Oumaima Alaoui Ismaili, Antoine Cornuéjols
2015 B conf
IJCNN
Christophe Salperwyck, Marc Boullé, Vincent Lemaire
2015 conf
EGC
Cedric Thao, Nicolas Voisine, Vincent Lemaire, Romain Trinquart
2015 conf
I-KNOW
Christian Beyer, Georg Krempl, Vincent Lemaire
2015 J jnl
CoRR
Patrick Luciano, Ismail Rebai, Vincent Lemaire
2015 conf
EGC (best of volume)
Carine Hue, Marc Boullé, Vincent Lemaire
2015 J jnl
Mach. Learn.
Georg Krempl, Daniel Kottke, Vincent Lemaire
2014 conf
ICONIP (1)
Oumaima Alaoui Ismaili, Vincent Lemaire, Antoine Cornuéjols
2014 conf
eBISS
Vincent Lemaire, Christophe Salperwyck, Alexis Bondu
2014 conf
EGC
Carine Hue, Marc Boullé, Vincent Lemaire
2014 conf
EGC
Christophe Salperwyck, Vincent Lemaire, Carine Hue
2014 B conf
IJCNN
Isabelle Guyon, Demian Battaglia, Alice Guyon, Vincent Lemaire, Javier G. Orlandi, Bisakha Ray, Mehreen Saeed, Jordi Soriano, Alexander R. Statnikov, Olav Stetter
2014 conf
Neural Connectomics
Javier G. Orlandi, Bisakha Ray, Demian Battaglia, Isabelle Guyon, Vincent Lemaire, Mehreen Saeed, Alexander R. Statnikov, Olav Stetter, Jordi Soriano
2014 J jnl
SIGKDD Explor.
Georg Krempl, Indre Zliobaite, Dariusz Brzezinski, Eyke Hüllermeier, Mark Last, Vincent Lemaire, Tino Noack, Ammar Shaker, Sonja Sievi, Myra Spiliopoulou, Jerzy Stefanowski
2014 conf
ECDA
Oumaima Alaoui Ismaili, Vincent Lemaire, Antoine Cornuéjols
2013 ch.
Statistical Models for Data Analysis
Christophe Salperwyck, Vincent Lemaire
2013 B conf
IJCNN
Laurent Candillier, Vincent Lemaire
2013 conf
EGC
Christophe Salperwyck, Marc Boullé, Vincent Lemaire
2013 conf
ECDA
Christophe Salperwyck, Vincent Lemaire, Carine Hue
2013 B conf
IJCNN
Christophe Salperwyck, Vincent Lemaire
2012 J jnl
Neural Networks
Isabelle Guyon, Gideon Dror, Vincent Lemaire, Daniel L. Silver, Graham W. Taylor, David W. Aha
2012 conf
ICML Unsupervised and Transfer Learning
Daniel L. Silver, Isabelle Guyon, Graham W. Taylor, Gideon Dror, Vincent Lemaire
2012 conf
EGC
Vincent Lemaire, Nicolas Creff, Fabrice Clérot
2012 ed.
ICML Unsupervised and Transfer Learning
Isabelle Guyon, Gideon Dror, Vincent Lemaire, Graham W. Taylor, Daniel L. Silver
2011 ed.
Active Learning and Experimental Design @ AISTATS
Isabelle Guyon, Gavin C. Cawley, Gideon Dror, Vincent Lemaire, Alexander R. Statnikov
2011 B conf
IJCNN
Christophe Salperwyck, Vincent Lemaire
2011 conf
Active Learning and Experimental Design @ AISTATS
Isabelle Guyon, Gavin C. Cawley, Gideon Dror, Vincent Lemaire
2011 B conf
IJCNN
Isabelle Guyon, Gideon Dror, Vincent Lemaire, Graham W. Taylor, David W. Aha
2010 B conf
IJCNN
Vincent Lemaire, Marc Boullé, Fabrice Clérot, Pascal Gouzien
2010 J jnl
Knowl. Inf. Syst.
Alexis Bondu, Marc Boullé, Vincent Lemaire
2010 conf
AAFD
Christophe Salperwyck, Vincent Lemaire
2010 B conf
IJCNN
Isabelle Guyon, Gavin C. Cawley, Gideon Dror, Vincent Lemaire
2010 B conf
IJCNN
Alexis Bondu, Vincent Lemaire, Marc Boullé
2010 A* conf
ICDM
Raphaël Féraud, Marc Boullé, Fabrice Clérot, Françoise Fessant, Vincent Lemaire
2010 conf
EGC
Alexis Bondu, Vincent Lemaire, Marc Boullé
2009 conf
KDD Cup
Isabelle Guyon, Vincent Lemaire, Marc Boullé, Gideon Dror, David Vogel
2009 J jnl
SIGKDD Explor.
Isabelle Guyon, Vincent Lemaire, Marc Boullé, Gideon Dror, David Vogel
2009 conf
EGC
Vincent Lemaire, Carine Hue
2009 ed.
KDD Cup
Gideon Dror, Marc Boullé, Isabelle Guyon, Vincent Lemaire, David Vogel
2008 A* conf
ICDM
Alexis Bondu, Marc Boullé, Vincent Lemaire, Stéphane Loiseau, Béatrice Duval
2008 B conf
IJCNN
Alexis Bondu, Vincent Lemaire
2008 B conf
IJCNN
Vincent Lemaire, Raphaël Féraud, Nicolas Voisine
2008 book
Vincent Lemaire
2007 A* conf
ICDM
Alexis Bondu, Vincent Lemaire, Barbara Poulain
2007 conf
EGC
Alexis Bondu, Vincent Lemaire, Barbara Poulain
2007 conf
GfKl
Françoise Fessant, Vincent Lemaire, Fabrice Clérot
2007 J jnl
Int. J. Imaging Syst. Technol.
Benedicte Bascle, Olivier Bernier, Vincent Lemaire
2007 conf
EGC
Vincent Lemaire, Raphaël Féraud
2006 conf
ICONIP (2)
Benedicte Bascle, Olivier Bernier, Vincent Lemaire
2006 ch.
Feature Extraction
Vincent Lemaire, Fabrice Clérot
2006 conf
ICONIP (2)
Vincent Lemaire, Raphaël Féraud
2006 conf
EuroIMSA
Nicolas Bonnel, Vincent Lemaire, Alexandre Cotarmanac'h, Annie Morin
2006 conf
IWICPAS
Benedicte Bascle, Olivier Bernier, Vincent Lemaire
2006 conf
AAFD
Alexis Bondu, Vincent Lemaire
2005 B conf
IJCNN
Vincent Lemaire, Fabrice Clérot, Sylvain Busson, Rozenn Nicol, Vincent Choqueuse
2005 ch.
Classification and Clustering for Knowledge Discovery
Vincent Lemaire, Fabrice Clérot
2004 B conf
IJCNN
Vincent Lemaire, Fabrice Clérot
2002 conf
FSKD
Vincent Lemaire, Fabrice Clérot
2000 J jnl
Neural Process. Lett.
Vincent Lemaire, Olivier Bernier, Daniel Collobert, Fabrice Clérot
1998 conf
ICIP (1)
Olivier Bernier, Michel Collobert, Raphaël Féraud, Vincent Lemaire, Jean-Emmanuel Viallet, Daniel Collobert
APK_CODE_ANALYSIS_PDD.md
← Index APK_CODE_ANALYSIS_PDD.md markdown
# APK Code Analysis — Product Design Document

**Author:** Engineering Team
**Date:** 2026-03-07
**Status:** Draft
**Target:** redb ingestor pipeline
**Depends on:** APK_FEATURES_PDD.md (APK static analysis extractors — implemented)

---

## 1. Overview

This document describes the design for adding **DEX code analysis** (decompilation, disassembly, call graphs, cross-references, and function similarity) to the redb ingestor pipeline. This is the Android equivalent of the Binary Ninja code analysis pipeline that exists for PE and ELF binaries.

### 1.1 Goals

- Decompile and disassemble APK DEX bytecode at the **method level**, producing per-method content and reference records analogous to the Binary Ninja `code_binja_*` tables
- Extract **call graphs and cross-references** (caller/callee relationships) for each method
- Compute **function similarity hashes** (SHA-256, ssdeep, TLSH, MinHash) for method-level clustering and hunting
- **Filter out library/framework code** to focus on user-written application logic — same philosophy as the `is_lib_or_thunk()` filter in Binary Ninja analysis
- Produce **decompiled Java source** (via JADX) and **smali disassembly** (via apktool) for each method, following the content/reference split pattern used by Binary Ninja tables
- Integrate with the existing APK extractor pipeline (runs after the Phase 1 APK extractors from `APK_FEATURES_PDD.md`)

### 1.2 Non-Goals

- **Native .so library analysis** — These are equivalent to external DLLs/shared libraries in PE/ELF. They are catalogued by `APKNativeLibExtractor` but not decompiled. If deep native analysis is needed, the existing ELF pipeline can be used on extracted `.so` files in a future phase.
- **Dynamic analysis / emulation** — Out of scope
- **Full APK repackaging / patching** — We use apktool for disassembly only, not rebuild
- **Inter-procedural data-flow analysis** (e.g., FlowDroid taint tracking) — Future consideration

### 1.3 Relationship to Existing Work

| Existing | New (this PDD) |
|----------|----------------|
| `APK_FEATURES_PDD.md` — APK metadata, manifest, permissions, certificates, DEX summary, resources, native libs | DEX **code-level** analysis: per-method decompilation, disassembly, call graphs, similarity hashes |
| `DecompileBinja` — PE/ELF code analysis via Binary Ninja | `DecompileAPK` — APK/DEX code analysis via androguard + JADX + apktool |
| `code_binja_*` ClickHouse tables | `code_apk_*` ClickHouse tables (same content/reference split pattern) |

---

## 2. Background

### 2.1 DEX Bytecode vs Native Code

| Aspect | PE/ELF (Binary Ninja) | APK/DEX (This PDD) |
|--------|----------------------|---------------------|
| Code format | Machine code (x86, ARM) | Dalvik bytecode (register-based VM) |
| Basic unit | Function (by address) | Method (by class + signature) |
| Disassembly | x86/ARM mnemonics | Smali (Dalvik assembly) |
| Decompilation | Pseudo-C (HLIL) | Java source code |
| Library filtering | `is_lib_or_thunk()` — symbol type | Package prefix filtering (e.g., `android.*`, `androidx.*`, `com.google.*`) |
| Similarity hashing | SHA-256 of normalized disassembly | SHA-256 of normalized smali |

### 2.2 Tool Selection

Three tools are combined to replicate the Binary Ninja analysis depth:

| Tool | Role | Integration | License |
|------|------|-------------|---------|
| **Androguard** (Python library) | Method enumeration, call graphs, cross-references, bytecode access, permissions analysis | Direct Python import — `from androguard.misc import AnalyzeAPK` | Apache 2.0 |
| **JADX** (Java CLI) | High-quality Java decompilation (equivalent to Binary Ninja HLIL) | subprocess (following CAPA/DIE pattern) | Apache 2.0 |
| **apktool** (Java CLI) | Smali disassembly with resource decoding (equivalent to Binary Ninja disassembly) | subprocess (following CAPA/DIE pattern) | Apache 2.0 |

**Why all three:**
- **Androguard** is the analysis engine — it provides call graphs, xrefs, and method enumeration natively in Python. However, its decompiler (DAD) produces lower-quality Java than JADX.
- **JADX** produces the best Java decompilation available. It is the industry standard for Android reverse engineering (47k+ GitHub stars).
- **apktool** produces canonical smali output with decoded resources. While androguard can access bytecode, apktool's smali output is the standard interchange format for Android RE.

### 2.3 Library Filtering Strategy

Native `.so` libraries are **not reverse-engineered** — they are equivalent to external DLLs in PE or shared libraries in ELF, and are already inventoried by `APKNativeLibExtractor`.

For DEX code, we filter out **framework/library packages** to focus on user-written code. This is the Android equivalent of `is_lib_or_thunk()` in the Binary Ninja pipeline.

**Default filter list** (configurable via environment variable `APK_LIBRARY_PREFIXES`):

```
android.*              # Android SDK
androidx.*             # AndroidX support libraries
com.google.android.*   # Google Play Services, Firebase
com.google.firebase.*  # Firebase
com.google.gson.*      # Gson JSON library
com.google.protobuf.*  # Protocol Buffers
kotlin.*               # Kotlin stdlib
kotlinx.*              # Kotlin extensions
org.apache.*           # Apache Commons
com.squareup.*         # OkHttp, Retrofit, Moshi
io.reactivex.*         # RxJava
org.reactivestreams.*  # Reactive Streams
com.facebook.*         # Facebook SDK
com.crashlytics.*      # Crashlytics
io.fabric.*            # Fabric
org.junit.*            # Test frameworks
org.mockito.*          # Test frameworks
```

Methods in filtered packages are still counted in call graph edges (caller/callee arrays) but their content is not stored in content tables. This mirrors how Binary Ninja records calls to library functions in `functions_caller`/`functions_call` arrays without decompiling the library functions themselves.

### 2.4 Packer Detection

Packer/protector detection for APKs uses **DetectItEasy (DIE)**, consistent with how packer detection works for PE/ELF/Mach-O in the existing pipeline. DIE already has signatures for common Android packers (Qihoo 360, Bangcle, Ijiami, Tencent Legu, Baidu, etc.).

The existing `DIEExtractor` runs as a format-agnostic extractor before format-specific analysis and requires no changes.

---

## 3. Architecture

### 3.1 Extractor Class Hierarchy

```
Extractor (redb/extractors/extractor.py)
└── DecompileAPK (NEW — redb/extractors/decompiler/DecompileAPK.py)
    ├── Uses: APKCodeAnalyzer (NEW — redb/extractors/decompiler/apk/analyzer.py)
    │   ├── AndroguardAnalysis — call graphs, xrefs, method enumeration
    │   ├── JADXDecompiler — Java decompilation (subprocess)
    │   └── ApktoolDisassembler — smali extraction (subprocess)
    └── Produces: multi_table ClickHouse export (same pattern as DecompileBinja)
```

**Design rationale:** `DecompileAPK` extends `Extractor` directly (not `APKExtractor`) because it follows the `DecompileBinja` pattern — a standalone extractor with its own analysis engine, rather than an APK metadata extractor that shares a parsed `APK` object. The APK parsing object from androguard is used internally but not shared with other extractors.

### 3.2 Analysis Pipeline Flow

```
APK file
  │
  ├─[1]─► apktool d <apk> ─► smali files on disk (temp dir)
  │
  ├─[2]─► jadx <apk> --no-res ─► Java source files on disk (temp dir)
  │
  └─[3]─► androguard AnalyzeAPK() ─► Analysis object (in-memory)
              │
              ├── Method enumeration ──► filter library packages
              │
              ├── For each user method:
              │     ├── Read smali from apktool output [1]
              │     ├── Read Java source from JADX output [2]
              │     ├── Get xrefs from Analysis object [3]
              │     ├── Compute content hashes (SHA-256 of smali, SHA-256 of Java)
              │     ├── Compute similarity hashes (ssdeep, TLSH of smali)
              │     └── Emit content + reference records
              │
              └── Call graph export ──► caller/callee arrays per method
```

Steps [1], [2], and [3] run in parallel (apktool and JADX as subprocess, androguard in-process). All three must complete before per-method analysis begins.

### 3.3 Content/Reference Split Pattern

Following the Binary Ninja schema pattern exactly:

- **Content tables** — Keyed by `function_hash` (SHA-256 of the method content). Deduplicated: if two APKs share identical method code, only one content record exists.
- **Reference tables** — Keyed by `(sha256, method_hash)`. Links a specific binary to its methods. Contains per-binary metadata (method name, class, address, callers, callees, fuzzy hashes).

This is the same pattern as `code_binja_decompiled_functions_content` / `code_binja_decompiled_functions_references`.

### 3.4 Method-Level Hashing

Hashing is computed at the **method level** for consistency with the Binary Ninja pipeline:

| Hash | Input | Purpose |
|------|-------|---------|
| `decompiled_method_hash` | SHA-256 of decompiled Java source (whitespace-normalized) | Content deduplication, exact match |
| `smali_method_hash` | SHA-256 of smali body (instructions only, no `.method`/`.end method` directives) | Content deduplication, exact match |
| `ssdeep_smali` | ssdeep of smali body | Fuzzy similarity search |
| `tlsh_smali` | TLSH of smali body | Fuzzy similarity search |
| `minhash_smali` | MinHash signature of smali instruction n-grams | LSH-based similarity clustering |

### 3.5 Obfuscation Indicators (per method)

Computed from the smali representation:

- `short_method_name` — Method name is <= 2 characters (a, b, c — typical R8/ProGuard output)
- `short_class_name` — Enclosing class has a single-letter name
- `has_string_encryption` — Method contains `const-string` followed by decryption-pattern calls
- `has_reflection_calls` — Method uses `java.lang.reflect.*` APIs
- `excessive_goto_count` — Number of `goto` instructions exceeds threshold (control flow flattening indicator)

---

## 4. Data Model

### 4.1 New Dataclasses

```python
@dataclass
class APKDecompiledMethodContent:
    """Decompiled Java source for a single method (content table — deduplicated by hash)."""
    decompiled_method_hash: str          # SHA-256 of normalized Java source
    decompiled_method: str               # Full Java method source
    method_type: str                     # "USER" or "LIBRARY"
    has_string_encryption: bool = False
    has_reflection_calls: bool = False
    excessive_goto_count: bool = False


@dataclass
class APKDecompiledMethodReference:
    """Links a specific APK to one of its decompiled methods (reference table)."""
    sha256: str                          # APK hash
    sha1: str
    md5: str
    decompiled_method_hash: str          # FK to content table
    smali_method_hash: Optional[str]     # FK to smali content table
    class_name: str                      # e.g., "com.example.MainActivity"
    method_name: str                     # e.g., "onCreate"
    method_signature: str                # e.g., "(Landroid/os/Bundle;)V"
    method_prototype: str                # e.g., "void onCreate(Bundle)"
    functions_caller: List[str]          # Methods that call this method
    functions_call: List[str]            # Methods called by this method


@dataclass
class APKSmaliMethodContent:
    """Smali disassembly for a single method (content table — deduplicated by hash)."""
    smali_method_hash: str               # SHA-256 of normalized smali body
    smali_method: str                    # Full smali method body
    method_type: str                     # "USER" or "LIBRARY"
    instructions_count: int = 0
    register_count: int = 0
    has_string_encryption: bool = False
    has_reflection_calls: bool = False
    excessive_goto_count: bool = False


@dataclass
class APKSmaliMethodReference:
    """Links a specific APK to one of its smali methods (reference table)."""
    sha256: str
    sha1: str
    md5: str
    smali_method_hash: str               # FK to content table
    decompiled_method_hash: Optional[str] # FK to decompiled content table
    class_name: str
    method_name: str
    method_signature: str
    ssdeep_smali: Optional[str] = None
    tlsh_smali: Optional[str] = None


@dataclass
class APKMethodSimilarityMetrics:
    """Similarity hashes for method-level clustering (keyed by smali hash)."""
    smali_method_hash: str
    cyclomatic_complexity: Optional[int] = None
    ssdeep_smali: Optional[str] = None
    tlsh_smali: Optional[str] = None
    minhash: Optional[List[int]] = None


@dataclass
class APKCodeAnalysisError:
    """Error encountered during method analysis."""
    sha256: str
    class_name: Optional[str] = None
    method_name: Optional[str] = None
    error_location: str = ""             # "jadx", "apktool", "androguard", "analysis"
    error_message: Optional[str] = None
    error_type: Optional[str] = None
```

### 4.2 Tag Enum Addition

```python
# In redb/extractors/enum.py
APK_DECOMPILED = "apk_decompiled"
```

### 4.3 ClickHouse Tables

| Table | Key | Pattern | Analog |
|-------|-----|---------|--------|
| `code_apk_decompiled_methods_content` | `decompiled_method_hash` | Content (deduplicated) | `code_binja_decompiled_functions_content` |
| `code_apk_decompiled_methods_references` | `(sha256, decompiled_method_hash)` | Reference (per-binary) | `code_binja_decompiled_functions_references` |
| `code_apk_smali_methods_content` | `smali_method_hash` | Content (deduplicated) | `code_binja_disassembled_functions_content` |
| `code_apk_smali_methods_references` | `(sha256, smali_method_hash)` | Reference (per-binary) | `code_binja_disassembled_functions_references` |
| `code_apk_method_similarity_metrics` | `smali_method_hash` | Similarity | `code_binja_function_similarity_metrics` |
| `code_apk_analysis_errors` | `(sha256, class_name, method_name)` | Errors | `function_analysis_errors_binja` |

All tables use `ReplacingMergeTree(analysis_date)` engine, consistent with existing schema.

---

## 5. External Tool Management

### 5.1 JADX

- **Invocation:** `jadx --no-res --no-imports --threads-count 2 --output-dir <tmpdir> <apk_path>`
- **Flags:**
  - `--no-res` — Skip resource decompilation (androguard handles resources)
  - `--no-imports` — Omit import statements for cleaner per-method extraction
  - `--threads-count 2` — Limit threads (same as Binary Ninja worker thread limit)
- **Output:** Java source files in `<tmpdir>/<package>/<Class>.java`
- **Timeout:** Configurable via `JADX_TIMEOUT` env var (default: 600s)
- **Path:** Configurable via `JADX_PATH` env var (default: `jadx`)
- **Error handling:** If JADX fails for a specific APK, the decompiled content tables are skipped but smali analysis continues. Error logged to `code_apk_analysis_errors`.

### 5.2 apktool

- **Invocation:** `apktool d --no-res --force --output <tmpdir> <apk_path>`
- **Flags:**
  - `--no-res` — Skip resource decoding (only want smali)
  - `--force` — Overwrite output directory if exists
- **Output:** Smali files in `<tmpdir>/smali/com/example/ClassName.smali` (one per class, containing all methods)
- **Timeout:** Configurable via `APKTOOL_TIMEOUT` env var (default: 600s)
- **Path:** Configurable via `APKTOOL_PATH` env var (default: `apktool`)
- **Error handling:** Same as JADX — if apktool fails, smali content tables are skipped but decompiled Java analysis continues. Error logged.

### 5.3 Androguard

- **Invocation:** Direct Python API — `AnalyzeAPK(filepath)` returns `(APK, list[DEX], Analysis)`
- **The `Analysis` object provides:**
  - `get_methods()` — All `MethodAnalysis` objects
  - `get_call_graph()` — networkx `MultiDiGraph` of method calls
  - `MethodAnalysis.get_xref_from()` — Who calls this method
  - `MethodAnalysis.get_xref_to()` — What this method calls
  - `MethodAnalysis.get_method()` — Access to `EncodedMethod` for bytecode
- **No timeout needed** — runs in-process, same Python process

---

## 6. Ingestor Integration

In `workers.py:process_binary_file()`, the APK branch will be extended to run `DecompileAPK` after the existing APK extractors:

```python
# Existing APK extractors (from APK_FEATURES_PDD.md)
for module in apk_modules:
    extractor = module(filepath, logger, exporters=exporters, ...)
    extractor.export_data()

# NEW: Code analysis (this PDD)
if "DecompileAPK" in selected_modules or "all" in selected_modules:
    decompiler = DecompileAPK(
        filepath, logger, exporters=exporters,
        index_prefix=index_prefix, filetype="apk",
    )
    decompiler.export_data()
```

The `DecompileAPK` extractor runs with its own timeout (configurable via `APK_DECOMPILE_TIMEOUT`, default: 1800s) using the same daemon-thread pattern as `DecompileBinja`.

---

## 7. New Dependencies

### 7.1 Required (system-level)

| Tool | Installation | Version | License | Purpose |
|------|-------------|---------|---------|---------|
| **JADX** | System package or download from GitHub releases | >= 1.5 | Apache 2.0 | Java decompilation |
| **apktool** | System package or download from GitHub releases | >= 2.9 | Apache 2.0 | Smali disassembly |
| **Java Runtime** | System package (`openjdk-17-jre` or similar) | >= 11 | GPL+CE | Required by JADX and apktool |

### 7.2 Required (Python — already installed)

| Library | Current Version | Usage in this PDD |
|---------|----------------|-------------------|
| `androguard` | >=4.1 | Call graphs, xrefs, method enumeration (already in requirements.txt) |
| `ppdeep` | installed | ssdeep fuzzy hashing (already used by Binary Ninja pipeline) |
| `py-tlsh` | installed | TLSH fuzzy hashing (already used by Binary Ninja pipeline) |
| `mmh3` | installed | MinHash computation (already used by Binary Ninja pipeline) |
| `networkx` | installed via androguard | Call graph representation (transitive dependency) |

### 7.3 No new Python dependencies required

All Python libraries needed are already in `requirements.txt`. The only new system-level dependencies are JADX, apktool, and a Java runtime.

---

## 8. Implementation Phases

### Phase 1 — Core Infrastructure

1. `APKCodeAnalyzer` class — androguard integration (method enumeration, call graph, xrefs, library filtering)
2. `JADXDecompiler` wrapper — subprocess management with timeout, output parsing
3. `ApktoolDisassembler` wrapper — subprocess management with timeout, smali parsing
4. Method-level content extraction and hashing logic
5. Unit tests for all Phase 1 components

### Phase 2 — Extractor and Data Export

6. `DecompileAPK` extractor class (following `DecompileBinja` pattern)
7. ClickHouse table creation functions
8. Multi-table export (`prepare_export_data`) for all 6 tables
9. Integration with `workers.py` dispatch
10. Unit tests for extractor, schema, and export
11. Update `TEST_INDEX.md`

### Phase 3 — Similarity and Obfuscation Analysis

12. Method-level similarity hash computation (ssdeep, TLSH, MinHash on smali)
13. Obfuscation indicator computation per method
14. `code_apk_method_similarity_metrics` table population
15. Unit tests for similarity and obfuscation
16. Update `TEST_INDEX.md`

### Phase 4 — Integration Testing and Hardening

17. End-to-end integration tests with real APK samples (benign + malicious + obfuscated)
18. Edge case handling: multi-DEX, empty DEX, packed APKs, APKs with no user code
19. Performance profiling and timeout tuning
20. Final `TEST_INDEX.md` update

---

## 9. Testing Strategy

### 9.1 Unit Tests

All unit tests mock external tools (JADX, apktool, androguard) and require no system dependencies:

- **Analyzer tests** — Method enumeration, library filtering, call graph extraction, xref parsing
- **JADX wrapper tests** — Subprocess invocation, output parsing, timeout handling, error recovery
- **Apktool wrapper tests** — Same as JADX
- **Hashing tests** — SHA-256 normalization, ssdeep/TLSH computation, MinHash signature generation
- **Extractor tests** — `DecompileAPK.extract()`, `prepare_export_data()`, multi-table schema validation
- **Smali parsing tests** — Method boundary detection, instruction extraction, register counting

### 9.2 Integration Tests

Require JADX, apktool, and Java installed:

- Full pipeline run on known APK samples
- Cross-validate decompiled output against known method signatures
- Verify ClickHouse export column counts and types
- Test with obfuscated APKs (ProGuard/R8 output)

### 9.3 Markers

```python
@pytest.mark.apk           # All APK tests
@pytest.mark.decompile      # All decompiler tests
@pytest.mark.unit           # No external deps
@pytest.mark.integration    # Requires JADX/apktool/Java
```

---

## 10. Configuration

All configuration via environment variables, consistent with existing extractors:

| Variable | Default | Description |
|----------|---------|-------------|
| `JADX_PATH` | `jadx` | Path to JADX binary |
| `JADX_TIMEOUT` | `600` | JADX subprocess timeout (seconds) |
| `APKTOOL_PATH` | `apktool` | Path to apktool binary |
| `APKTOOL_TIMEOUT` | `600` | apktool subprocess timeout (seconds) |
| `APK_DECOMPILE_TIMEOUT` | `1800` | Overall decompilation timeout (seconds) |
| `APK_LIBRARY_PREFIXES` | (see §2.3) | Comma-separated package prefixes to filter |
| `APK_MIN_METHOD_INSTRUCTIONS` | `5` | Minimum smali instruction count to analyze a method |

---

## 11. Open Questions / Future Work

1. **ProGuard/R8 mapping file support** — If mapping files are bundled (rare in malware, common in crash reports), JADX can use them to restore original names. Deferred.
2. **Kotlin-specific analysis** — Kotlin metadata annotations could provide richer type information. Deferred.
3. **Cross-DEX analysis** — Multi-DEX APKs may have cross-DEX method calls. Androguard handles this via `AnalyzeAPK()` which loads all DEX files into a single `Analysis` object. No special handling needed.
4. **JADX as Java library via JPype** — Could eliminate subprocess overhead. Deferred in favor of the proven subprocess pattern, but may be revisited if performance is an issue.

---

## Appendix A — CFG Feature Parity with Binary Ninja Pipeline

**Date:** 2026-03-13
**Status:** Planned (Phase 5)
**Depends on:** Phases 13 complete

### A.1 Motivation

The Binary Ninja pipeline produces a dedicated `code_binja_cfg_functions` table with 17 fields capturing graph topology, structural hashes, and per-block feature vectors. The current APK pipeline computes only basic graph scalars (`block_count`, `edge_count`, `cyclomatic_complexity`, `loop_count`, `max_depth`, `max_fan_out`) and bundles them into the `code_apk_method_similarity_metrics` table alongside fuzzy hashes.

Analysis shows that **all advanced CFG features can be computed from smali** — this is not a limitation of Java bytecode. The existing APK infrastructure already:

- Builds `successors[]` adjacency lists from smali control flow (`smali_cfg.py`)
- Computes per-block ACFG feature vectors using the same 8-category schema as Binary Ninja (`smali_cfg.py:_build_block_features`)
- Normalizes Dalvik opcodes into semantic categories equivalent to LLIL categories (`smali_normalization.py`)

The generic functions in `cfg_features.py` (`compute_topology_hash`, `compute_md_index_topdown/bottomup`, `compute_wl_minhash`, `compute_cfg_feature_tlsh`, `pack_adjacency`) operate on adjacency lists and block feature arrays — they have no Binary Ninja dependency and can be called directly from the APK pipeline.

### A.2 Table Restructuring

Split the current single table into two, mirroring the Binja pattern:

#### `code_apk_method_similarity_metrics` (content-based fuzzy matching)

Retains only fuzzy hashes and instruction-sequence similarity data:

| Column | Type | Change |
|--------|------|--------|
| `smali_method_hash` | FixedString(64) | Unchanged |
| `cyclomatic_complexity` | Nullable(UInt16) | Stays (duplicated in both, same as Binja) |
| `ssdeep_smali` | Nullable(String) | Unchanged |
| `tlsh_smali` | Nullable(FixedString(72)) | Unchanged |
| `minhash` | Array(UInt8) | Unchanged |
| `analysis_date` | DateTime64(3, 'UTC') | Unchanged |

Removed from this table: `block_count`, `edge_count`, `loop_count`, `max_depth`, `max_fan_out` — these move to the CFG table.

#### `code_apk_cfg_methods` (NEW — structural/topological similarity)

Mirrors `code_binja_cfg_functions`:

| Column | Type | Source | Analog in Binja |
|--------|------|--------|-----------------|
| `smali_method_hash` | FixedString(64) | Existing | `disassembled_function_hash` |
| `cfg_topology_hash` | FixedString(16) | NEW — `cfg_features.compute_topology_hash()` | Same |
| `block_count` | UInt16 | Moved from similarity table | Same |
| `edge_count` | UInt16 | Moved from similarity table | Same |
| `instructions_count` | UInt32 | Existing (total Dalvik instructions) | `llil_total_operations` |
| `call_count` | UInt16 | NEW — count of `invoke-*` instructions | Same |
| `cyclomatic_complexity` | UInt16 | Moved from similarity table | Same |
| `loop_count` | UInt8 | Moved from similarity table | Same |
| `max_depth` | UInt16 | Moved from similarity table | Same |
| `max_fan_out` | UInt8 | Moved from similarity table | Same |
| `md_index_topdown` | UInt64 | NEW — `cfg_features.compute_md_index_topdown()` | Same |
| `md_index_bottomup` | UInt64 | NEW — `cfg_features.compute_md_index_bottomup()` | Same |
| `prime_product_smali` | UInt64 | NEW — Dalvik opcode → prime mapping | `prime_product_llil` |
| `cfg_feature_tlsh` | Nullable(FixedString(72)) | NEW — `cfg_features.compute_cfg_feature_tlsh()` | Same |
| `wl_minhash` | Array(UInt8) | NEW — `cfg_features.compute_wl_minhash()`, 128 elements | Same |
| `bb_features` | Array(Array(UInt16)) | Existing (computed, not exported) | Same |
| `cfg_adjacency` | Array(UInt32) | NEW — `cfg_features.pack_adjacency()` | Same |
| `analysis_date` | DateTime64(3, 'UTC') | | Same |

### A.3 Naming Differences from Binja

Two columns are intentionally renamed to reflect what the data actually represents:

- **`prime_product_smali`** (not `prime_product_llil`) — the prime mapping is applied to normalized Dalvik opcodes, not LLIL. Semantically equivalent for APK-to-APK comparison but not numerically comparable to Binja values.
- **`instructions_count`** (not `llil_total_operations`) — counts Dalvik instructions, not LLIL operations. LLIL decomposes machine instructions into sub-operations; Dalvik bytecode is already at a higher abstraction level where one instruction ≈ one operation.

### A.4 Implementation Requirements

| Task | Effort | Notes |
|------|--------|-------|
| Build `predecessors[]` from `successors[]` in `smali_cfg.py` | ~5 lines | Trivial reverse mapping |
| Define `SMALI_OP_PRIMES` mapping | ~30 lines | Map semantic categories from `smali_normalization.py` to same primes used in `cfg_features.py` |
| Wire `cfg_features.py` functions into `smali_cfg.py` | ~40 lines | Call `compute_topology_hash`, `compute_md_index_*`, `compute_wl_minhash`, `compute_cfg_feature_tlsh`, `pack_adjacency` |
| Export `bb_features` (already computed, not exported) | ~5 lines | Add to results dict |
| Count `invoke-*` instructions for `call_count` | ~5 lines | Filter in instruction loop |
| New `code_apk_cfg_methods` table export in `DecompileAPK.py` | ~60 lines | Follow existing export pattern |
| Slim down `code_apk_method_similarity_metrics` export | ~10 lines | Remove moved columns |
| ClickHouse schema for new table | ~30 lines | Mirror `code_binja_cfg_functions` |
| Unit tests | ~100 lines | Test new fields, reuse patterns from `test_cfg_features.py` |

**Total estimated: ~285 lines of code changes.**

### A.5 What Cannot Be Identical Cross-Platform

The `prime_product_smali` values are **not numerically comparable** to `prime_product_llil` from the Binja pipeline. LLIL decomposes native instructions into sub-operations (e.g., one x86 `push` becomes `STORE` + `SET_REG`), while Dalvik bytecode maps 1:1 to semantic categories. The prime products are valid for APK-vs-APK similarity and APK-vs-APK clustering, which is the intended use case.

All other fields (`cfg_topology_hash`, `md_index_*`, `wl_minhash`, `cfg_feature_tlsh`, `bb_features`, `cfg_adjacency`) are computed from the same generic algorithms and are structurally equivalent across platforms.