Zobrazeno 1 - 10
of 3 825
pro vyhledávání: '"A. Nachiappan"'
Autor:
Harzevili, Nima Shiri, Mohajer, Mohammad Mahdi, Shin, Jiho, Wei, Moshi, Uddin, Gias, Yang, Jinqiu, Wang, Junjie, Wang, Song, Ming, Zhen, Jiang, Nagappan, Nachiappan
Checker bugs in Deep Learning (DL) libraries are critical yet not well-explored. These bugs are often concealed in the input validation and error-checking code of DL libraries and can lead to silent failures, incorrect results, or unexpected program
Externí odkaz:
http://arxiv.org/abs/2410.06440
Autor:
Abreu, Rui, Murali, Vijayaraghavan, Rigby, Peter C, Maddila, Chandra, Sun, Weiyan, Ge, Jun, Chinniah, Kaavya, Mockus, Audris, Mehta, Megh, Nagappan, Nachiappan
Release engineering has traditionally focused on continuously delivering features and bug fixes to users, but at a certain scale, it becomes impossible for a release engineering team to determine what should be released. At Meta's scale, the responsi
Externí odkaz:
http://arxiv.org/abs/2410.06351
Software-Defined Networks (SDN) are the standard architecture for network deployment. Intrusion Detection Systems (IDS) are a pivotal part of this technology as networks become more vulnerable to new and sophisticated attacks. Machine Learning (ML)-b
Externí odkaz:
http://arxiv.org/abs/2406.06099
Autor:
Dunay, Omer, Cheng, Daniel, Tait, Adam, Thakkar, Parth, Rigby, Peter C, Chiu, Andy, Ahmad, Imad, Ganesan, Arun, Maddila, Chandra, Murali, Vijayaraghavan, Tayyebi, Ali, Nagappan, Nachiappan
CodeCompose is an AI-assisted code authoring tool powered by large language models (LLMs) that provides inline suggestions to 10's of thousands of developers at Meta. In this paper, we present how we scaled the product from displaying single-line sug
Externí odkaz:
http://arxiv.org/abs/2402.04141
Autor:
Rigby, Peter C., Rogers, Seth, Saleem, Sadruddin, Suresh, Parth, Suskin, Daniel, Riggs, Patrick, Maddila, Chandra, Nagappan, Nachiappan
Code review ensures that a peer engineer manually examines the code before it is integrated and released into production. At Meta, we develop a wide range of software at scale, from social networking to software development infrastructure, such as ca
Externí odkaz:
http://arxiv.org/abs/2312.17169
Autor:
Li, Peizhao, He, Junfeng, Li, Gang, Bhargava, Rachit, Shen, Shaolei, Valliappan, Nachiappan, Liang, Youwei, Gu, Hongxiang, Ramachandran, Venky, Farhadi, Golnaz, Li, Yang, Kohlhoff, Kai J, Navalpakkam, Vidhya
Progress in human behavior modeling involves understanding both implicit, early-stage perceptual behavior, such as human attention, and explicit, later-stage behavior, such as subjective preferences or likes. Yet most prior research has focused on mo
Externí odkaz:
http://arxiv.org/abs/2312.10175
Publikováno v:
Benchmarking: An International Journal, 2023, Vol. 31, Issue 9, pp. 2984-3011.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/BIJ-10-2022-0614
Autor:
Belhadi, Amine, Kamble, Sachin, Subramanian, Nachiappan, Singh, Rajesh Kumar, Venkatesh, Mani
Publikováno v:
International Journal of Operations & Production Management, 2024, Vol. 44, Issue 11, pp. 1946-1982.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/IJOPM-11-2022-0737
Automatic detection of software bugs is a critical task in software security. Many static tools that can help detect bugs have been proposed. While these static bug detectors are mainly evaluated on general software projects call into question their
Externí odkaz:
http://arxiv.org/abs/2307.04080
Autor:
Harzevili, Nima Shiri, Belle, Alvine Boaye, Wang, Junjie, Wang, Song, Ming, Zhen, Jiang, Nagappan, Nachiappan
Software vulnerability detection is critical in software security because it identifies potential bugs in software systems, enabling immediate remediation and mitigation measures to be implemented before they may be exploited. Automatic vulnerability
Externí odkaz:
http://arxiv.org/abs/2306.11673