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10 papers · 1 filter

cs.SE2025

Characterizing Build Compromises Through Vulnerability Disclosure Analysis

Maimouna Tamah Diao, Moustapha Awwalou Diouf, Iyiola Emmanuel Olatunji +4

The software build process transforms source code into deployable artifacts, representing a critical yet vulnerable stage in software development. Build infrastructure security pos…

cs.CV2025

Beyond Real Faces: Synthetic Datasets Can Achieve Reliable Recognition Performance without Privacy Compromise

Paweł Borsukiewicz, Fadi Boutros, Iyiola E. Olatunji +4

The deployment of facial recognition systems has created an ethical dilemma: achieving high accuracy requires massive datasets of real faces collected without consent, leading to d…

cs.SE2025

Human-Aligned Code Readability Assessment with Large Language Models

Wendkûuni C. Ouédraogo, Yinghua Li, Xueqi Dang +6

Code readability is crucial for software comprehension and maintenance, yet difficult to assess at scale. Traditional static metrics often fail to capture the subjective, context-s…

cs.CR2025

MalLoc: Toward Fine-grained Android Malicious Payload Localization via LLMs

Tiezhu Sun, Marco Alecci, Aleksandr Pilgun +5

The rapid evolution of Android malware poses significant challenges to the maintenance and security of mobile applications (apps). Traditional detection techniques often struggle t…

cs.SE2025

Boosting Open-Source LLMs for Program Repair via Reasoning Transfer and LLM-Guided Reinforcement Learning

Xunzhu Tang, Jacques Klein, Tegawendé F. Bissyandé

Several closed-source LLMs have consistently outperformed open-source alternatives in program repair tasks, primarily due to their superior reasoning capabilities and extensive pre…

cs.SE2025

Beyond Surface Similarity: Evaluating LLM-Based Test Refactorings with Structural and Semantic Awareness

Wendkûuni C. Ouédraogo, Yinghua Li, Xueqi Dang +5

Large Language Models (LLMs) are increasingly used to refactor unit tests, improving readability and structure while preserving behavior. Evaluating such refactorings, however, rem…

cs.SE2025

Rethinking Cognitive Complexity for Unit Tests: Toward a Readability-Aware Metric Grounded in Developer Perception

Wendkûuni C. Ouédraogo, Yinghua Li, Xueqi Dang +5

Automatically generated unit tests-from search-based tools like EvoSuite or LLMs-vary significantly in structure and readability. Yet most evaluations rely on metrics like Cyclomat…

cs.CL2025

Memorization or Interpolation ? Detecting LLM Memorization through Input Perturbation Analysis

Albérick Euraste Djiré, Abdoul Kader Kaboré, Earl T. Barr +2

While Large Language Models (LLMs) achieve remarkable performance through training on massive datasets, they can exhibit concerning behaviors such as verbatim reproduction of train…

cs.SE2025

Programming Language Confusion: When Code LLMs Can't Keep their Languages Straight

Micheline Bénédicte Moumoula, Serge Lionel Nikiema, Abdoul Kader Kabore +2

Large Language Models (LLMs) have achieved state-of-the-art performance across software engineering tasks, from code generation to translation. However, we identify and systematica…

cs.CR2025

Software Security in Software-Defined Networking: A Systematic Literature Review

Moustapha Awwalou Diouf, Samuel Ouya, Jacques Klein +1

Software-defined networking (SDN) separates the control plane from the data plane and exposes the network through software applications and open APIs. The same programmability that…