Unfair behaviors of Machine Learning (ML) software have garnered increasing attention and
concern among software engineers. To tackle this issue, extensive research has been …

Today, many industrial processes are undergoing digital transformation, which often
requires the integration of well-understood domain models and state-of-the-art machine …

Federated learning (FL) is an emerging, privacy-preserving machine learning paradigm,
drawing tremendous attention in both academia and industry. A unique characteristic of FL …

Contribution: A novel undergraduate course design at the intersection of software
engineering (SE) and machine learning (ML) based on industry-reported challenges …

Serverless computing is an emerging paradigm for cloud computing, gaining traction in a
wide range of applications such as video processing and machine learning. This new …

This study on politeness and morals is a learning strategy used in the interaction between
santri and kyai/ustdaz in Pesantren Salaf Al-Qur'an Sholahul Huda Al-Mujahidin. This study …

Federated learning (FL) becomes a promising machine learning paradigm. The impact of
heterogeneous hardware specifications and dynamic states on the FL process has not yet …

Abstract Machine learning and deep learning models are commonly developed using
programming languages such as Python, C++, or R and deployed as web apps delivered …

WebAssembly (abbreviated WASM) has emerged as a promising language of the Web and
also been used for a wide spectrum of software applications such as mobile applications …

WebAssembly (abbreviated as Wasm) was initially introduced for the Web and quickly
extended its reach into various domains beyond the Web. To create Wasm applications …