Impact Score 3.13
With the rapid development of software technology and people's increasing enthusiasm for programming, the open, flexible and efficient community group development method has been recognized and popularized all over the world. A large number of excellent open-source software that brings together group wisdom has emerged and is widely used. Under such a development trend, many project participants collaborate with each other and their interests are related to each other, gradually forming various open-source software ecosystems which has become an important research content in software engineering. Due to the large scale of the open-source software ecosystems, the activities of its participants are complicated, and the capabilities of developers are different. Moreover, its data has the characteristics of heterogeneous, multi-modal and dynamics. These characteristics bring challenges to the research on open-source software ecosystems. So, there is a growing necessity to develop more optimized methodologies that are able to process these data and deal with various problems in software ecosystems. Meanwhile, deep learning is revolutionizing numrous research areas, such as computer vision, natural language processing, and pattern recognition, etc., because it is capable to extracting useful data, discriminating parameters, and knowledge representations, benefitting from the availability of the very large datasets. Thus, it is critical to explore deep learning techniques to address above challenges in open-source software ecosystem analytics.
This special issue aims to contribute to bring together the state-of-the-art deep learning research contributions that address the key aspects of open-source software ecosystem analytics. We focus on more accurate and explainable solutions which are potential for deployment in a range of future open-source software ecosystem applications.
The topics of interest include, but not limited to:
Manuscript submission deadline: June 15, 2021
Round 1 Decisions: Sept 15, 2021
Prof. Honghao Gao, Shanghai University, China (Lead Guest Editor)
Prof. Alex Zhang, University of Auckland, New Zealand
Prof. Ramón J. Durán Barroso, Universidad de Valladolid, Spain
Prof. Xiong Luo, University of Science and Technology Beijing, China