7 papers · ranked by Valyu relevance
Qihong Song, Haize Hu, Tebo Dai
Code search aims to search for code snippets from large codebase that are semantically related to natural query statements. Deep learning is a valuable method for solving code search tasks in which the quality of training data directly impacts the performance of deep-learning models. However, most existing…
Muhammad Hammad, Önder Babur, Hamid Abdul Basit, Mark van den Brand + 1 more
'Yilun Shang'] Software developers frequently reuse source code from repositories as it saves development time and effort. Code clones (similar code fragments) accumulated in these repositories represent often repeated functionalities and are candidates for reuse in an exploratory or rapid development. To facilitate…
Anastasia Drozdova, Ekaterina Trofimova, Polina Guseva, Anna Scherbakova + 2 more
The use of program code as a data source is increasingly expanding among data scientists. The purpose of the usage varies from the semantic classification of code to the automatic generation of programs. However, the machine learning model application is somewhat limited without annotating the code snippets. To address…
Nazia Bibi, Tauseef Rana, Ayesha Maqbool, Farkhanda Afzal + 3 more
'Ali Akgül' 'Manuel De la Sen' 'Rebeca P. Díaz\xa0Redondo'] The development of robotic applications necessitates the availability of useful, adaptable, and accessible programming frameworks. Robotic, IoT, and sensor-based systems open up new possibilities for the development of innovative applications, taking advantage…
Evangelos Vlachos, Elliot Lefkowitz
Background In order to designate the various concepts of taxa in biology, evolution and paleontology, scientists have developed various rules on how to create unique names for taxa. Different Codes of Nomenclature have been developed for animals, plants, fungi, bacteria etc., with standard sets of Rules that govern the…
Yiwen Zhang, Wei Liu, Fazhong Jiang, Jiquan Ma + 4 more
Large Language Models of the Transformer architecture display great promise in automated code error detection based on their strength in processing sequential data. Nevertheless, their efficacy could be further improved by addressing the inherent weakness in handling structural code dependencies. In response to this…
Valeriy Berezovskiy, Anastasia Gorodilova, Ekaterina Trofimova, Andrey Ustyuzhanin + 1 more
'Andrey Ustyuzhanin' 'Syed Hassan Shah'] Program code has recently become a valuable active data source for training various data science models, from code classification to controlled code synthesis. Annotating code snippets play an essential role in such tasks. This article presents a novel approach that leverages…