Glenn Jackson
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Glenn Jackson has a total of 9 co-authors. Here are the top co-authors by number of shared publications:
- Andrew McCarren
Dublin City University
1 shared publication - David Solan
FINEOS Corporation Limited, Dublin, Ireland
1 shared publication - Jim Buckley
University of Limerick
1 shared publication Marin Bivol
FourTheorem Limited, The Rubicon, Cork Institute of Technology, Cork, Ireland
1 shared publication- Murat Yilmaz
Gazi University
1 shared publication - Neil Lapuz
School of Computing, SFI Research Centre for Software, Dublin City University and Lero, Dublin, Ireland
1 shared publication
Latest Publications
- Top Cited PapersOpen Access
- 23 June 2023
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Software Engineering
- Vol. 49 (8) , 4213-4242
Decomposition of Monolith Applications Into Microservices Architectures: A Systematic Review
Microservices architecture has gained significant traction, in part owing to its potential to deliver scalable, robust, agile, and failure-resilient software products. Consequently, many companies that use large and complex software systems are actively looking for automated solutions to decompose their monolith applications into microservices. This paper rigorously examines 35 research papers selected from well-known databases using a Systematic Literature Review (SLR) protocol and snowballing method, extracting data to answer the research questions, and presents the following four contributions. First, the Monolith to Microservices Decomposition Framework (M2MDF) which identifies the major phases and key elements of decomposition. Second, a detailed analysis of existing decomposition approaches, tools and methods. Third, we identify the metrics and datasets used to evaluate and validate monolith to microservice decomposition processes. Fourth, we propose areas for future research. Overall, the findings suggest that monolith decomposition into microservices remains at an early stage and there is an absence of methods for combining static, dynamic, and evolutionary data. Insufficient tool support is also in evidence. Furthermore, standardised metrics, datasets, and baselines have yet to be established. These findings can assist practitioners seeking to understand the various dimensions of monolith decomposition and the community's current capabilities in that endeavour. The findings are also of value to researchers looking to identify areas to further extend research in the monolith decomposition space.
- 23 June 2023
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Software Engineering
- Vol. 49 (8) , 4213-4242
Top Cited PapersOpen AccessDecomposition of Monolith Applications Into Microservices Architectures: A Systematic Review
Microservices architecture has gained significant traction, in part owing to its potential to deliver scalable, robust, agile, and failure-resilient software products. Consequently, many companies that use large and complex software systems are actively looking for automated solutions to decompose their monolith applications into microservices. This paper rigorously examines 35 research papers selected from well-known databases using a Systematic Literature Review (SLR) protocol and snowballing method, extracting data to answer the research questions, and presents the following four contributions. First, the Monolith to Microservices Decomposition Framework (M2MDF) which identifies the major phases and key elements of decomposition. Second, a detailed analysis of existing decomposition approaches, tools and methods. Third, we identify the metrics and datasets used to evaluate and validate monolith to microservice decomposition processes. Fourth, we propose areas for future research. Overall, the findings suggest that monolith decomposition into microservices remains at an early stage and there is an absence of methods for combining static, dynamic, and evolutionary data. Insufficient tool support is also in evidence. Furthermore, standardised metrics, datasets, and baselines have yet to be established. These findings can assist practitioners seeking to understand the various dimensions of monolith decomposition and the community's current capabilities in that endeavour. The findings are also of value to researchers looking to identify areas to further extend research in the monolith decomposition space.