Muhammad Hassan (University of Illinois Urbana Champaign), Carl Gunter (University of Illinois Urbana Champaign), Susan Landau (Tufts University), Masooda Bashir (University of Illinois Urbana Champaign)

Matter seeks to resolve long-standing interoper-ability problems in the Internet of Things (IoT), yet little is known about how developers experience the standard in day-to-day work. This paper examines over 13,000 issues from the official Project CHIP GitHub repository to understand the kinds of problems contributors report when implementing and integrating Matter. Using topic modeling and qualitative analysis, we identify four recurring areas of concern—Testing, Interoperability, Development, and Platform & Network—and describe how they manifest in the evolution of the codebase and tooling. The findings reveal systematic technical and integration challenges and point to concrete opportunities to refine Matter’s test infrastructure, cross-vendor guidance, and documentation as the standard continues to mature.

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Was My Data Used for Training? Membership Inference in...

Xue Tan (Institute of Big Data, Fudan University, Shanghai, China and College of Computer Science and Artificial Intelligence, Fudan University, Shanghai, China), Hao Luan (Institute of Big Data, Fudan University, Shanghai, China and College of Computer Science and Artificial Intelligence, Fudan University, Shanghai, China), Mingyu Luo (Institute of Big Data, Fudan University, Shanghai, China and…

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Hiding an Ear in Plain Sight: On the Practicality...

Youqian Zhang (The Hong Kong Polytechnic University), Zheng Fang (The Hong Kong Polytechnic University), Huan Wu (The Hong Kong Polytechnic University & Technological and Higher Education Institute of Hong Kong), Sze Yiu Chau (The Chinese University of Hong Kong), Chao Lu (The Hong Kong Polytechnic University), Xiapu Luo (The Hong Kong Polytechnic University)

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NVLift: Lifting NVIDIA GPU Assembly to LLVM IR for...

Junpeng Wan, Louis Zheng-Hua Tan, Dave (Jing) Tian (Purdue University)

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