相关论文: Large-Scale Microtask Programming

We introduce Dynatask: an open source system for setting up custom NLP tasks that aims to greatly lower the technical knowledge and effort required for hosting and evaluating state-of-the-art NLP models, as well as for conducting model in…

When we consider the application layer of networked infrastructures, data and control flow are important concerns in distributed systems integration. Modularity is a fundamental principle in software design, in particular for distributed…

Microservices architecture is one of the new architectural styles that has improved in recent years. It has become a popular architectural style among system architects and developers. This popularity increased with the advent of new…

Models of crowdsourcing and human computation often assume that individuals independently carry out small, modular tasks. However, while these models have successfully shown how crowds can accomplish significant objectives, they can…

There has been significant interest in crowdsourcing and human computation. One subclass of human computation applications are those directed at tasks that involve planning (e.g. travel planning) and scheduling (e.g. conference scheduling).…

A common way of exposing functionality in contemporary systems is by providing a Web-API based on the REST API architectural guidelines. To describe REST APIs, the industry standard is currently OpenAPI-specifications. Test generation and…

The aim of this contribution is to analyse practical aspects of the use of REST APIs and gRPC to realize communication tasks in applications in microservice-based ecosystems. On the basis of performed experiments, classes of communication…

Crowdsourcing is widely used to create data for common natural language understanding tasks. Despite the importance of these datasets for measuring and refining model understanding of language, there has been little focus on the…

A self-adaptive system can dynamically monitor and adapt its behavior to preserve or enhance its quality attributes under uncertain operating conditions. This article identifies key challenges for the development of microservice…

This work-in-progress report presents both the design and partial evaluation of distributed execution indexing, a technique for microservice applications that precisely identifies dynamic instances of inter-service remote procedure calls…

Large language models and AI agents have recently shown promise in automating software performance optimization, but existing approaches predominantly rely on local, syntax-driven code transformations. This limits their ability to reason…

Crowdsourcing refers to the arrangement in which contributions are solicited from a large group of unrelated people. Due to this nature, crowdsourcers (or task requesters) often face uncertainty about the workers' capabilities which, in…

Although information workers may complain about meetings, they are an essential part of their work life. Consequently, busy people spend a significant amount of time scheduling meetings. We present Calendar.help, a system that provides…

We examine "vibe coding": an emerging programming paradigm where developers primarily write code by interacting with code-generating large language models rather than writing code directly. We present the first empirical study of vibe…

Distributed programs are hard to get right because they are required to be open, scalable, long-running, and tolerant to faults. In particular, the recent approaches to distributed software based on (micro-)services where different services…

Existing research in crowdsourcing has investigated how to recommend tasks to workers based on which task the workers have already completed, referred to as {\em implicit feedback}. We, on the other hand, investigate the task recommendation…

To evaluate how developers perform differently in solving programming tasks, i.e., which actions and behaviours are more beneficial to them than others and if there are any specific strategies and behaviours that may indicate good versus…

Session-based Recommendation (SR) aims to predict the next item for recommendation based on previously recorded sessions of user interaction. The majority of existing approaches to SR focus on modeling the transition patterns of items. In…

In this paper, we present a data-driven approach to generate realistic steering behaviors for virtual crowds in crowd simulation. We take advantage of both rule-based models and data-driven models by applying the interaction patterns…

In recent years modelling crowd and evacuation dynamics has become very important, with increasing huge numbers of people gathering around the world for many reasons and events. The fact that our global population grows dramatically every…