Zhang, Wei


Zhang, Wei

Associate Professor

Research Interests: Reuse-oriented requirements engineering, software development

Office Phone: 86-10-6275 9074

Email: zhangw.sei@pku.edu.cn

Zhang, Wei is an associate professor in the Department of Computer Science and technology, School of EECS. He obtained his B.Sc. from Nanjing University of Aeronautics and Astronautics in 1999, and Ph.D from Peking University in 2006, respectively. His research interests include reuse-oriented software requirements engineering, and Internet-based software development.

Dr. Zhang has published about 30 research papers, including RE, MODELS, ICSR, SPLC, REJ, IEEE Software, and Science China Information Sciences; two of these papers are selected as one of the best papers in 13th IEEE International Requirements Engineering Conference and 8th ACM/IEEE International Conference on Model Driven Engineering Languages & Systems, and one is selected as Best Research Paper Nominee in 12th International Conference on Software Reuse. He was awarded CCF Distinguished Ph.D Dissertation Award (2006), Second Prize of State Natural Science Award of P.R.China (2012), and Neosoft-NASAC Young Software Innovation Award (2015).

Dr. Zhang has 4 NSFC research projects, including a project supported by the State Key Program of National Natural Science of China, and a project supported by the Major Program of the National Natural Science Foundation of China. His research achievements are summarized as follows:

1)  Reveals the basic relations between different kinds of requirements dependencies, and between requirements-level architecture and design-level architecture. He utilizes feature models as the architecture for requirements organization, gives a definition of features from the two viewpoints of intension and extension, identifies four kinds of dependency between/among features, and proposes a method to transform feature models to software architecture. In a systematic survey about automated analysis of feature models in recent 20 years, the researchers point out the two concepts (atomic sets, and false optional features) in feature models are first proposed in his research papers.

2)  Proposes an approach to supporting the continual construction and evolution of model-based software artifacts by a collective of Internet-connected stakeholders. The key mechanism is incremental graph superimposition (IGS), a refinement of stigmergy, which is the process that produces collective intelligence in social insects. Employing IGS, a collective of individuals collaboratively and continually construct a collective-level graph by incrementally aggregating the individuals' working results. Each individual can work independently without direct interaction with others, facilitating mass collaboration among a large number of individuals. This approach has been used for collaborative modeling of conceptual models in software development.