14 papers · ranked by Valyu relevance
Muslim Chochlov, Gul Aftab Ahmed, James Vincent Patten, Yuanhua Han + 3 more
Source code clones pose risks ranging from intellectual property violations to unintended vulnerabilities. Effective and efficient scalable clone detection, especially for diverged clones, remains challenging. Large language models (LLMs) have recently been applied to clone detection tasks. However, the rapid emergence…
M. Shahbaz Ismail, Sara Shahzad, Fahmi H. Quradaa, Sajid Anwar
Semantic code clone detection plays an essential role in software maintenance and quality assurance, as it helps uncover fragments of code that express the same logic even when their syntax has been altered or deliberately obfuscated. In this study, we propose a framework that combines hybrid representation learning…
Zixian Zhang, Takfarinas Saber
—Code clone detection is a fundamental task in software engineering that underpins refactoring, debugging, plagiarism detection, and vulnerability analysis. Existing methods often rely on singular representations such as abstract syntax trees (ASTs), control flow graphs (CFGs), and data flow graphs (DFGs), which…
Zhiwei Xu, Weixian Deng, Xuyang Liu, Xiaolin Peng + 4 more
Code clone detection has been extensively studied for decades, and recent approaches have begun reporting remarkably high performance for semantic (Type-4) clones on benchmark datasets. However, it remains unclear whether these results reflect a genuine ability to capture semantic equivalence between programs, or…
Palash R. Roy, Banani Roy, Kevin A. Schneider, Chanchal K. Roy
The growing diversity of code clone types, from syntactic copies to cross-language semantic clones to AI-generated duplicates, has created a fragmentation crisis in clone detection. Current deep learning detectors are domain specialists that degrade significantly outside their training distribution, with F1 drops…
Roberto Rota, Elizabeth Flittner, Matteo Tartagni, Marwane Bourdim + 16 more
Experimental dissection of clonal dynamics in complex tissues requires barcoding systems that are scalable, compatible with different analytical platforms, providing phenotypic and spatial resolution. Here we introduce X-CODE, a dual-expressed RNA barcoding system designed to enable high-complexity clonal tracking…
Lachlan Cain, Anna S Trigos
Single-cell analyses of cancer typically begin by identifying distinct populations of cancer cells by unsupervised clustering. However, in many cases this clustering is explained simply by differences in DNA copy number, which affects the interpretation of differential expression results and tumour heterogeneity…
Daniele Lucarelli, Tina Kos, Caylie Shull, Sara Jiménez + 5 more
Expressed cellular barcoding systems paired with single cell readouts enable the tracking of clonal populations and associated transcriptomic changes across different conditions, such as genetic or therapeutic perturbations. To demonstrate QuiCAT’s versatility, we applied its reference-based workflow to capture and…
Ke Sun, Zhongyuan Guo, Hong Zheng, Cosimo Distante
Quick response codes are widely used as anti-counterfeiting labels in the field of product packaging, but they are easily illegally copied. Thus, this paper introduces a quick response code verification method that combines an anti-counterfeiting pattern with a deep feature fusion network. Firstly, a specialized…
Liyang Fei, Jovana Maksimovic, Alicia Oshlack, Macha Nikolski
Cellular DNA barcoding is a powerful cell clonal tracking (lineage tracing) technique also referred to as lineage tracing. It incorporates unique DNA barcodes into a cell’s genome, thereby genetically labelling each cell in a population (). The DNA barcodes are inherited by daughter cells, allowing the origin of each…
Farhia Kabeer, Matteo Lepur, Branden J. Lynch, Emilia Hurtado + 13 more
Circulating cell-free DNA (cfDNA) offers a minimally invasive lens into tumor evolution. However, the accurate quantification of clonal composition from cfDNA remains challenging. Existing methods for clone tracking using liquid biopsies are constrained by issues such as their reliance on bulk tissue references…
Sergey Isaev, Alek G Erickson, Igor Adameyko, Peter V Kharchenko
Assays coupling high-throughput lineage tracing with single-cell transcriptomics are transforming studies of development and disease biology, revealing not only major differentiation routes but also continuous fate biases and their putative regulators. Yet, analysis of such data at scale presents challenges due to the…
Shalini Raj Unnikandam Veettil, Joanna Donatelli, Geetansh Kalra, Constanza Verónica Ljubetic San Martín + 9 more
The generation of clonal CHO cell lines is foundational to biologics manufacturing; however, labor-intensive cell culture workflows predominate in the field. We created the CLAIRE (Cell Line AI Recognition and Evaluation) tool to streamline end-to-end cell line development by integrating deep-learning image analysis…
Zhengbin Zou, Tao Jiang, Yizheng Wang, Tiancheng Xue + 2 more
The increasing complexity of software systems has rendered code vulnerability detection a critical aspect of software security. While deep learning-based approaches have advanced this field, challenges such as coarse-grained function-level detection, scalability limitations, and constrained accuracy persist. Although…