Research

Software security research with practical reach.

The lab studies vulnerabilities, malware, code clones, software evolution, and testing at scales ranging from individual functions to billions of lines of code.

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01Explore Roadmap

Cyber Security

Source-level assessment methods for identifying, understanding, and mitigating software vulnerabilities.

02Explore Roadmap

Vulnerability Detection

Scalable techniques and tools that trace vulnerable code through patches, fingerprints, and code similarity.

03Explore Roadmap

Software Testing

Search-based testing, automated test-data generation, regression testing, and test-smell detection.

04Explore Roadmap

Malware Detection

Static and learning-based analysis of Android and cross-architecture malware at source-code level.

05Explore Roadmap

Code Clone Analysis

Large-scale detection of exact, near-miss, and obfuscated code clones across software systems.

06Explore Roadmap

Software Evolution & Reuse

Understanding how code, vulnerabilities, and reusable components propagate between systems.

Research workflow

From source evidence to validated outcomes

Stage 01 — Evidence

Source Artifact Ingestion

Repositories, CVE benchmarks, smart contracts, APKs & patch histories

Stage 02 — Analysis

AST & Semantic Parsing

Control/data flow graphs, clone detection & obfuscation normalization

Stage 03 — Detection

Vulnerability Engine

Isolating security flaws, malware behaviors & test smells (SQVDT, VCIPR)

Stage 04 — Validation

Empirical Benchmarking

Precision/recall evaluation, CWE ground truths & patch verification

Stage 05 — Transfer

Publications & Supervised Projects

Q1 journal papers, open-source tools deployment & student supervision

Projects & tools

Current and completed research platforms

Research project · University of Luxembourg & SES (Postdoctoral Research 2021–2023)

Automated Test Data Generation for the ARC System

A model-based approach and tool for generating and validating complex CPS test data using random, search-based, constraint-based, and mutation strategies.

Software Verification and Validation Lab (SnT), University of Luxembourg, and SES, Luxembourg.
Completed · 2021–2023

Test Smell Detection in the ARC System

Tool-supported detection of poor testing practices in multi-level, BDD-based testing frameworks to improve test definition and maintainability.

Software Verification and Validation Lab (SnT), University of Luxembourg, and SES, Luxembourg.
Completed · 2021–2022

Log-Based Test Case Slicing

A tool-supported approach for decomposing complex system tests into smaller scenarios while preserving their assertions and reducing regression-test execution cost.

Software Verification and Validation Lab (SnT), University of Luxembourg.
Completed · 2018–2020

Obfuscated Code Detection in Android Applications

A clone-detection approach for identifying identifier-renaming and string-encryption obfuscation in Android source code, evaluated across obfuscated and non-obfuscated datasets.

Key Laboratory of Information System Security, School of Software, Tsinghua University.
Completed · 2018–2020

SQVDT — Source Code Vulnerability Detection

A file-level platform built from a fingerprint index of 2,931 vulnerable files and evaluated across 7 TB of C/C++ source code from 152,823 open-source projects.

Key Laboratory of Information System Security, School of Software, Tsinghua University.
Completed · 2017–2018

VCIPR — Vulnerability Detection at Function Level

A scalable, token-based and language-independent tool for detecting vulnerable and unpatched code fragments at function-level granularity.

Key Laboratory of Information System Security, School of Software, Tsinghua University.
Completed · 2018–2020

Patch Analysis and Vulnerability Research

A structured benchmark that traces open-source security patches and extracts vulnerable source code at function, file, and component granularity for repeatable security assessment.

Key Laboratory of Information System Security, School of Software, Tsinghua University.
Completed · 2015–2017

DroidSD — Android Similarity Detection

A source-level clone-detection tool for identifying Type-1, Type-2, and Type-3 clones in a dataset of 30,500 Android applications.

Key Laboratory of Information System Security, School of Software, Tsinghua University.
Completed · 2015–2017

IBFET — Large-Scale Code Clone Detection

An index-based feature extraction technique evaluated over more than 324 billion lines of code in a Hadoop distributed environment.

Key Laboratory of Information System Security, School of Software, Tsinghua University.