Dr Feng Chen

Job: Senior Lecturer

Faculty: Computing, Engineering and Media

School/department: School of Computer Science and Informatics

Research group(s): Cyber Technology Institute (CTI) (Software Technology Research Laboratory STRL))

Address: De Montfort University, The Gateway, Leicester, LE1 9BH, United Kingdom

T: +44 (0)116 257 7860

E: fengchen@dmu.ac.uk

W: https://www.dmu.ac.uk/cti


Personal profile

I was awarded my BSc, Mphil and PhD in computer science at Nankai University, Dalian University of Technology and De Montfort University in 1991, 1994 and 2007. My PhD thesis focuses on modernising legacy systems through model construction and transformation. A unified approach is proposed in the context of Model Driven Architecture (MDA) to extract different level of models from legacy source code. 

I have been an active researcher in the area of software engineering and knowledge engineering, focusing on its emerging themes including Service Oriented Architecture, Model Driven Architecture, Cloud/Edge Computing, Mobile Computing, Internet of Things and Cyber Physical System, with the long term aim of building a coherent set of conceptual frameworks, methods and tool support for the development of Smart Environments and Ambient Assisted Living Systems. 

I have a strong background in a combination of academic research and industrial application. I have gained invaluable understanding of system software, distributed systems, real-time systems, critical systems and security systems through many projects. As research outputs, I have published 74 research papers in refereed conferences and Journals.

Research group affiliations

Cyber Technology Institute

Publications and outputs

  • Survey of IP-based air-to-ground data link communication technologies
    dc.title: Survey of IP-based air-to-ground data link communication technologies dc.contributor.author: Özmen, Sergun; Hamzaoui, Raouf; Chen, Feng dc.description.abstract: The main purpose of an air traffic management system is to provide air traffic services to an aircraft moving within the controlled airspace. Very high frequency (VHF) radio in continental regions, as well as high frequency (HF) radio and satellite communications in remote areas, are used today as the primary way of delivering air traffic services. The technical limitations and constraints associated with the current technology, such as line-of-sight requirement, vulnerability to interference, and limited coverage, cause degraded voice quality and discontinuity in service. At the same time, voice-based communication may affect flight safety due to poor language skills, call sign confusion, and failure to use standard phraseology. For this reason, text-based communication over a VHF data link (VDL) has been proposed as an alternative. However, it is predicted that VDL will be insufficient to support increasing air traffic and intensive data exchanges due to its lack of mobility support and limited resources to ensure service continuity. This paper surveys next-generation data link technologies based on the current state of the "industry standard" for aeronautical communication. These include Aeronautical Mobile Airport Communication System (AeroMACS), L-band Digital Aeronautical Communications System (LDACS), and Airborne New Advanced Satellite Techniques & Technologies in a System Integrated Approach (ANASTASIA). The paper also surveys IP-based text communication solutions over these next-generation data links. We analyze the efficiency of the proposed solutions with regard to service continuity and aeronautical application requirements. We conclude the survey by identifying open problems and future trends. dc.description: open access article
  • Component Profiling and Prediction Models for QoS-Aware Self-Adapting DSMS Framework
    dc.title: Component Profiling and Prediction Models for QoS-Aware Self-Adapting DSMS Framework dc.contributor.author: Yagnik, Tarjana; Chen, Feng; Kasraian, Laleh dc.description.abstract: Quality of Service (QoS) has been identified as an important attribute of system performance of Data Stream Management Systems (DSMS). A DSMS should have the ability to allocate physical computing resources between different submitted queries and fulfil QoS specifications in a fair and square manner. System scheduling strategies need to be adjusted dynamically to utilise available physical resources to guarantee the end-to-end quality of service levels. In this paper, we present a proactive method that utilises a multi-level component profiling approach to build prediction models that anticipate several QoS violations and performance degradations. The models are constructed using several incremental machine learning algorithms that are enhanced with ensemble learning and abnormal detection techniques. The approach performs accurate predictions in near real-time with accuracy up to 85% and with abnormal detection techniques, the accuracy reaches 100%. This is a major component within a proposed QoS-Aware Self-Adapting Data Stream Management Framework.
  • QoS-Aware Self-Adapting Resource Utilisation Framework for Distributed Stream Management Systems
    dc.title: QoS-Aware Self-Adapting Resource Utilisation Framework for Distributed Stream Management Systems dc.contributor.author: Yagnik, Tarjana; Chen, Feng; Kasraian, Laleh dc.description.abstract: The last decade witnessed plenty of Big Data processing and applications including the utilisation of machine learning algorithms and techniques. Such data need to be analysed under specific Quality of Service (QoS) constraints for certain critical applications. Many frameworks have been proposed for QoS management and resource allocation for the various Distributed Stream Management Systems (DSMS), but lack the capability of dynamic adaptation to fluctuations in input data rates. This paper presents a novel QoS-Aware, Self-Adaptive, Resource Utilisation framework which utilises instantaneous reactions with proactive actions. This research focuses on the load monitoring and analysis parts of the framework. By applying real-time analytics on performance and QoS metrics, the predictive models can assist in adjusting resource allocation strategies. The experiments were conducted to collect the various metrics and analyse them to reduce their dimensions and identify the most influential ones regarding the QoS and resource allocation schemes.
  • Agentification for web services
    dc.title: Agentification for web services dc.contributor.author: Chen, Feng; Yang, Hongji; Guo, He; Xu, Baowen dc.description.abstract: We report our effort on the AgenEvo project, which develops an evolution approach to re-engineer legacy systems into agent-based Web services. We first survey the key technologies, which are adopted in this paper. After discussing the basic features of the Web services and agent, we focus on agent-based Web services, which are hot spot in web-based research area. We argue that agent-based Web services are well suited to building software solutions for distributed, open and dynamic web-based systems. Next, we introduce our approach on re-engineering framework and working flow. The method that integrates agents with Web services for legacy system evolution is proposed and an example on how to use agent-based Web services software evolution framework and methodology to re-engineer the legacy system is illustrated. Finally, we conclude the paper and suggest the directions of the possible future research.
  • Agent-based Web services evolution for pervasive computing
    dc.title: Agent-based Web services evolution for pervasive computing dc.contributor.author: Liu, Ruimin; Chen, Feng; Yang, Hongji; Chu, William Cheng-chung; Lai, Yu-Bin dc.description.abstract: Pervasive computing will be a fertile source of challenging research problems in computer systems for many years to come. The ability to obtain services and information from an environment anywhere at anytime is part of pervasive computing. The problem is that most of existing services and applications are designed for stationary PCs. How to evolve these so called legacy system towards those mobile users in a controlled manner is vital for that pervasive computing can become more widespread. In this paper, we report our efforts on the PerEvo project. After discussing the basic features and challenges of pervasive computing, we present an agent-based Web services evolution approach, which is well suited to building software solutions for pervasive computing, and illustrate our solutions through a booking scenario.
  • Feature analysis for service-oriented reengineering
    dc.title: Feature analysis for service-oriented reengineering dc.contributor.author: Chen, Feng; Li, Shaoyun; Yang, Hongji; Wang, Ching-Huey; Chu, William Cheng-chung dc.description.abstract: Web services together with service-oriented architectures (SOA) are playing an important role in the future of distributed computing, significantly impacting software development and evolution. With the adoption to Web services technology, more and more existing non-service-oriented software systems turn to be legacy systems. They require a service-oriented reengineering process in order to survive in service-oriented computing environment. If the reengineering goal is to expose the services of a single object or any underlying function-oriented middleware, many problems will arise including semantic mismatches, service granularity issues and state management. Attempting to masquerade software assets from a lower level of abstraction can often cause significant mismatch and exposure problems. In this paper, by using feature analysis, an approach to supporting service-oriented reengineering is presented. Service identification and packaging process are performed and resulted into a service delegation.
  • A Formal Model Driven Approach to Dependable Software Evolution
    dc.title: A Formal Model Driven Approach to Dependable Software Evolution dc.contributor.author: Chen, Feng; Yang, Hongji; Qiao, Bing; Chu, William Cheng-chung dc.description.abstract: The paper proposes a unified formal model driven approach to software evolution based on both program transformation and model transformation of legacy systems. A formal model definition ensures a consistent interpretation of the legacy system and provides a theoretical foundation for dependable software evolution. The theoretical foundation is based on the construction of a wide spectrum language for reengineering, known as WSL, which enjoys a sound formal semantics. The architecture and working flow of the approach are proposed, and the mappings between WSL and PSL in MDA provide an engaging combination of traditional program transformation and modern model transformation, which shows that the proposed approach is feasible and promising in its domain. A prototype tool is developed to test the approach and a case study is used for experiments with the proposed approach and the prototype tool. Conclusion is drawn based on analysis and further research directions are also discussed
  • Model oriented evolutionary redocumentation
    dc.title: Model oriented evolutionary redocumentation dc.contributor.author: Chen, Feng; Yang, Hongji dc.description.abstract: This paper discusses aspects of the redocumentation of legacy systems and proposes a model oriented approach to generating documentation, which is to produce models from existing systems and to generate the documentation based on the models. Since the software models can bridge the gap of a legacy system and an evolved system, the generated documentation covers all the information of system evolution. A prototype software redocumentation tool is presented to semi-automate this process and a case study of a system in IBM assembler is used for experiments with the approach and the prototype tool.
  • A Home-Based IoT-Enabled Framework for Sleep Behaviour Assessment
    dc.title: A Home-Based IoT-Enabled Framework for Sleep Behaviour Assessment dc.contributor.author: Fallmann, Sarah; Chen, Liming; Chen, Feng dc.description.abstract: Sleep has an impact on a person's life including their health and wellbeing, thus assessing sleep behaviour is of high importance to gain insight into people's general health status. In general, current sleep behaviour assessment is restricted to a controlled scenario within a hospital environment limited by the time of monitoring and to specific factors. As healthcare is shifting from reactive to preventive and predictive care with the support of digital health and IoT technology, there is a growing demand to make sleep assessment possible at home. In this paper, we propose a sleep behaviour assessment framework considering different facets of sleep such as sleep quality, regularity, circadian rhythm, environmental conditions and sleep hygiene. Hence, we describe methodologies and techniques which can help realise home-based sleep assessment. A salient feature of the framework is that it takes into account personal preferences and influential factors as well as doctor's recommendations and clinical history, thus, allowing personalised medical and behavioural assessment. In addition, the proposed framework supports a modular service-oriented design adaptable to both doctor and user needs and availability of underpinning technologies.
  • ICA-Based EEG Feature Analysis and Classification of Learning Styles
    dc.title: ICA-Based EEG Feature Analysis and Classification of Learning Styles dc.contributor.author: Alhasan, Khawla; Aliyu, Suleiman; Chen, Liming; Chen, Feng dc.description.abstract: A thorough investigation of the electroencephalograph (EEG) information may support an enriched awareness of the mechanism of understanding different learning styles patterns. Wavelet analysis is a powerful technique that uniquely permits the decomposition of complex information of trends, discontinuities, a repeated pattern. The purpose of such methods is to be able to assign simple segments at diverse locations and scales, to be remodelled afterward effectively. In this paper, we attempt to classify individual cognitive learning styles using artificial neural networks and unsupervised learning. First, we apply Independent component analysis (ICA) to extract relevant features (artefacts removal) of the EEG records. We analyse the ICA-based EEG channels data using inter-quartiles to show the degree of dispersion and skewness. Next, self-organising maps (SOM) are then created to characterise different cognitive learning styles from selected ICA-based channel data.

Click here to view a full listing of Feng Chen's publications and outputs.

Key research outputs


Research interests/expertise

Software Engineering

Software Re-engineering

Distributed Computing

Software Evolution

Software Architecture

Program/Model Transformation

Domain Specific Modelling

Knowledge Engineering

Areas of teaching

Software Engineering 


2015 to 2016, PGCertHE, De Montfort University, UK

Apr. 2003 to Jul. 2007, Doctor of Philosophy in Software Engineering, Software Technology Research Laboratory (STRL), De Montfort University, UK

Sep. 1991 to Jul. 1994, Master Degree in Computer Science, Computer Science and Engineering Department, Dalian University of Technology, China

Sep. 1987 to Jul. 1991, Bachelor Degree in Computer Science, Computer Science Department, NanKai University, China

Courses taught

Postgraduate Course:

Advanced Requirements Engineering and Software Architecture/ Requirement Analysis and Cloud-based Systems

Software Project Management and Testing/ Software Quality Assurance and Testing

Undergraduate Course:

Server and Storage Solutions,

Lab of Java Programming/ OO Software Design 

Membership of professional associations and societies

IEEE Membership


SOCRADES EU Project, EU Research project, 03/2009-03/2010. The developed engineering tool was used by Ford UK Ltd.

SPADzeroTM Sign Communication Control System for Dailys UK Ltd., 06/2007-12/2007. SPADzeroä is a stand-alone executable software product for data distribution to remote display.

FermaT Integrated Platform (FIPfor Software Maintenance Ltd. (SML), UK, 07/2005–06/2007. The software product has been used for program analysis, demonstration and training by SML.

SIFT Project for Fuji Film Company, 04/2004-10/2004. The developed image processing software package was tested and delivered to Fuji Film Company.

PLC Simulation System for 2000t/d Cement Product Line, 06/2002-12/2002. The system was used by Beijing Building Materials Industry School for teaching and training.

MIS for Environmental Protection Administration, 08/2001-12/2002. The system was installed in Dalian and Dandong Bureau of Environmental Protection Administration. The software won the Second Class of Dalian Information System Application Prize, China.

Multi-interface Virtual Operating System Based on Windows (VRTOS), 02/2001-02/2002. VRTOS was used for developing W-CDMA and 3G protocol stack in Dalian HuaChang Electronics & Communication Technology Co. Ltd., China.

IC Card Tax Declaration System, 06/1998-12/1999. The system was filed as a practical new style patent of China, titled “General Smart Card Declaration Terminal” (ZL 96 2 39055.0).

Counselling System for Entry-Exit Inspection and Quarantine, 08/1995-02/1996. The Software was awarded Golden Snake Prize in 1996. The software was used by Dalian Entry-Exit Inspection and Quarantine for more than 10 years.

Phosphate Elimination Control System for Prominent GMBH, Germany, Research project, Part of BMFT Grant (02WA9029/1). 01/1995-07/1995. The neuro-fuzzy learning algorithm based controller was installed in Heldelberg sewage plant, Germany to improve the effort of biological phosphate elimination and reduces 30% usage of the chemical dosage.

Conference attendance

Local Chair, IEEE Smart World Congress (SWC2019)

General Chair2nd Workshop on advanced Technologies for Smarter Assisted Living solutions: Towards an open Smart Home infrastructure (SmarterAAL'19)

Program Co-Chair, IEEE International Conference on Ubiquitous Intelligence and Computing (UIC 2018), IEEE Outstanding Leadership Award

Program Chair, IEEE International Workshop on Software Cybernetics 2017 (IWSC2017)

Program Chair, IEEE International Workshop on Software Cybernetics 2016 (IWSC2016)

Technical program committee member, more than 10 international conferences

Key articles information

(IF=4.639) Triboan, D. Chen, L., Chen, F., Wang, Z. (2019) A semantics-based approach to sensor data segmentation in real-time Activity Recognition. Future Generation Computer Systems. 93, 224-236

(IF=3.557) Ding F., Liu Y., Chen X., Chen F. (2018). Rising Star Evaluation in Heterogeneous Social Network. IEEE Access. 6, 29436-29443

(IF=3.241) Zhang, Y., Guo, H., Chen, F., Yang, H. (2017) Weighted kernel mapping model with spring simulation based watershed transformation for level set image segmentation. Neurocomputing. 249, 1-18

(IF=2.278) Yang, H. Chen, F., Aliyu, Y. (2017) Modern software cybernetics: New trends. Journal of Systems and Software, 124, 169-186

(IF=1.924) Triboan, D. Chen, L., Chen, F., Wang, Z. (2017) Semantic segmentation of real-time sensor data stream for complex activity recognition. Personal and Ubiquitous Computing. 21(3), 411-425

Cope, J., Siewe, F., Chen, F., Maglaras, L., Janicke, H. (2017) On data leakage from non-production systems, Information & Computer Security, 25(4), 454-474, Emerald

Cope, J., Maglaras, L., Siewe, F., Chen, F., Janicke (2017) A Framework for Minimising Data Leakage from Non-Production Systems. Book chapter, In book: Bigdata Analytics: Tools and Technology for Effective Planning. Chapman and Hall/CRC.

Psychoula, I., Chen, L., Chen, F. (2017) “Privacy modelling and management for assisted living within smart homes”, e-Health Networking, Applications and Services (Healthcom), IEEE. (Best Paper)

(IF=1.063) Triboan, D. Chen, L., Chen, F., Wang, Z. (2016) Towards a Service-oriented Architecture for a Mobile Assistive System with Real-time Environmental Sensing. Tsinghua Science & Technology. 21(6), 581-597

Chen, F., Al-Bayatti, A., Siewe, F. (2016) Context-aware Cloud Computing for Personal Learning Environment. Book chapter, In book: Cloud-Based STEM Education for Improved Learning Outcomes, IGI Global.

(IF=0.613) Chen, F. et al. (2014) A Precondition-based Approach to Workflow Oriented Software Re-engineering. Computer Science and Information Systems, 11(1), 1-27

AlHakami, H., Chen, F., Janicke, H. (2014) An Extended Stable Marriage Problem Algorithm for Clone Detection. International Journal of Software Engineering & Applications (IJSEA). 5(4), 103-122

AlHakami, H., Chen, F., Janicke, H. (2014) SMP-Based Approach for Intelligent Service Interaction, International Journal of Advanced Computer Science and Applications (IJACSA). Special Issue on Extended Papers from Science and Information Conference 2014, 124-131

Current research students

Alhasan, Khawla  Second Supervisor

Aliyu, Suleiman  First Supervisor

Da Silva Machado, Eduardo  Second Supervisor

Fallmann, Sarah  Second Supervisor

Ma, Fengbao  First Supervisor

Psychoula, Ismini  Second Supervisor 

Singh, Lakhvir  Second Supervisor 

Triboan, Darpan  Second Supervisor

Yagnik, Tarjana  First Supervisor

Zheng, Yumei  Second Supervisor

Externally funded research grants information

"Acrossing - Advanced TeChnologies and PlatfoRm fOr Smarter ASsisted LivING" (2016-2019, € 3.8M, DMU € 810K). Co-I, Coordinator of EU Horizon 2020 project.

"Affordable Virtual Engineering Tools" (2014-2015, £60K). PI, TSB KTP project.

Internally funded research project information

“A Feasibility Study of the Use of Smart Textiles to Support Assistive Living” (2017-2018, £2K). PI, internal RIF project, De Montfort University, UK

Ÿ“Marketing of Professional Training Courses within Cyber Technologies” (3 months, 2016). Supervisor, Internship project, De Montfort University, UK

Published patents

"General Smart Card Declaration Terminal" (1998). A Practical New Style Patent of China (ZL 96 2 39055.0, First Order in Four Inventers).

Professional esteem indicators


IEEE Transactions on Reliability; Journal of Systems and Software (Elsevier);

Personal and Ubiquitous Computing Journal (Springer);

Journal of Software: Evolution and Process (Wiley);

Arabian Journal for Science and Engineering;

Journal of Ambient Intelligence and Humanized Computing (Springer);

Journal of Computational Methods in Sciences and Engineering (IOS). 


PhD external examiner: Masoud Khamallag, University of Bradford, Towards an Improved Framework of E-Government Implementation in Chaotic Environment; Proposed Social Collaboration Model. 2018

PhD external examiner: Richard Greenwell, Edinburgh Napier University, An Approach to the Semantic Intelligence Cloud. 2017

PhD internal examiner at De Montfort University: more than 10 students.


External academic panel member for Review of Course Provision: Postgraduate Computer Science and Technology, University of Bedfordshire, July 2016.

External academic panel member for a validation of BSc (Hons) Software Engineering and Network Engineering programmes at University Campus Suffolk in Ipswich, April 2015.