Avatars Grow Legs: Generating Smooth Human Motion from Sparse Tracking Inputs with Diffusion Model
Yuming Du, Robin Kips, Albert Pumarola, Sebastian Starke, Ali Thabet, Artsiom Sanakoyeu
International Conference on Software Maintenance and Evolution (ICSME)
Allowing developers to move fast when evolving and maintaining low-latency, large-scale distributed systems is a challenging problem due to i) sheer system complexity and scale, ii) degrading code quality, and iii) difficulty of performing reliable rapid change management while the system is in production. Addressing these problems has many benefits to increase system developer efficiency, reliability, performance, as well as code maintenance. In this paper, we present a real-world case study of an architectural refactoring project within an industrial setting. The system in scope is our codenamed ItemIndexer delivery system (I2DS), which is responsible for processing and delivering a large number of items at rapid speed to billions of users in real time. I2DS is running in production, refactored live over a period of 9 months, and assessed through impact validation studies that show a 42% improvement in developer efficiency, 87% improvement in reliability, 20% increase in item scoring, a 10% increase in item matching, and 14% CPU savings.
Yuming Du, Robin Kips, Albert Pumarola, Sebastian Starke, Ali Thabet, Artsiom Sanakoyeu
Lisa Rivalin, Andrew Grier, Tobias Tiecke, Chi Zhou, Doris Gao, Prakriti Choudhury, John Fabian
Shreshth Tuli, Kinga Bojarczuk, Natalija Gucevska, Mark Harman, Xiao-Yu Wang, Graham Wright