SCIENCE CHINA Information Sciences
Special Issue on Crowd-based Software Development in the Era of Big Data
Call for Papers

The rapid development of Internet and information technology has greatly changed the form and programming paradigms of traditional software systems. Modern software is eating the world with the significant trend of software-defined anything. Software communities on the Internet eliminate the boundaries between software developers and end users, and the crowds in these communities collaborate together to develop high quality software applications or systems with low cost by means of collective intelligence. New features of such crowd-based software development activities, such as open and equal status of different kinds of stakeholders, collective wisdom and efforts of all participants, dynamic evolution of software artifacts, and continuous accumulation of the data generated, are far beyond the scope of traditional software development theories and practice. In particular, large amounts of data generated in crowd-based software development processes, which posses the 4-V characteristics of big data, bring both huge challenges and great opportunities for the innovations of software development methods and techniques. Besides, all of these may have profound impacts on current software engineering education and practice, as well as on the reform in the future.

This special issue aims to provide a forum for researchers and practitioners in software engineering and related fields to disseminate their new ideas and research results, which address the crowd-based software development methods and technologies in the Big Data Era. We are soliciting original and unpublished high-quality research papers on topics of interest, but are not limited to the following main topics:
**Novel paradigms for crowd-based software development, e.g., software crowdsourcing and social programming
**Crowd-based software development lifecycle, models, and processes
**Emergence and evolution of collective intelligence in software communities
**Crowd-based software development methods for requirement elicitation, problem solving, software modeling and design, social programming, and software quality assurance (e.g., crowdsourced testing)
**Intelligent provisioning, delivery, deployment and runtime monitoring for software services (or cloud services) based on the crowd generated content in software communities
**Maintenance and evolution of software/service ecosystems in the Big Data Era
**Mining Software repositories for special-purpose knowledge discovery and reuse in crowd-based software development
**Value-driven analysis and application of big data generated in crowd-based software development processes
**Case study and empirical studies
**Massive open online courses (MOOCs) for crowd-based software development
**Interdisciplinary fields between software engineering and network science, big data, services computing, social science, etc.

Submission
Prospective authors should prepare their manuscripts in accordance with the format requirement for Science China Information Sciences according to the instructions given at the homepage of the journal (http://info.SciChina.com), and submit the PDF version of each completed manuscript through the manuscript submission site of the journal (http://mc03.manuscriptcentral.com/scis). All submissions will be reviewed by at least three reviewers in the peer review system of the journal.

Domestic authors from China (including Hong Kong, Taiwan, and Macao), who receive the first round of notification for their submissions, are required to present their papers at the sixth CCF (China Computer Federation) National Conference on Services Computing (NCSC 2015) to be held in October 2015.

Important Dates
Manuscript due: July 15, 2015
Round one notification: October 15, 2015
Revised manuscript due: November 20, 2015
Acceptance notification: December 5, 2015
Final manuscript due: December 30, 2015
Anticipated publication date: February 15, 2016

Guest Editors
Keqing He, Wuhan University, China, hekeqing@whu.edu.cn
Wei-Tek Tsai, Arizona State University, USA, wtsai@asu.edu
Wenjun Wu, Beihang University, China, wwj@nlsde.buaa.edu.cn