Fiona Hayes
- Artificial Intelligence top 5%
- Information Systems top 2%
- Software top 2%
- Computer Networks and Communications top 10%
- Computational Theory and Mathematics top 5%
- Co-authors
- Derek ColemanPatrick ArnoldDennis de ChampeauxPierre AmericaAntónio Rito SilvaRoger DukeGary T. LeavensDoug Lea
- Topics
- Model-Driven Software Engineering Techniques (4 papers)Software Engineering Research (4 papers)Logic, programming, and type systems (3 papers)
- Partner nations
- United KingdomUnited StatesGermany
In The Last Decade
Fiona Hayes
9 papers receiving 421 citations
Peers
Comparison fields: 5 of 46
- Artificial Intelligence 350
- Information Systems 297
- Software 232
- Computer Networks and Communications 108
- Computational Theory and Mathematics 91
Countries citing papers authored by Fiona Hayes
This map shows the geographic impact of Fiona Hayes's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Fiona Hayes with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fiona Hayes more than expected).
Fields of papers citing papers by Fiona Hayes
This network shows the impact of papers produced by Fiona Hayes. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Fiona Hayes. The network helps show where Fiona Hayes may publish in the future.
Co-authorship network of co-authors of Fiona Hayes
This figure shows the co-authorship network connecting the top 25 collaborators of Fiona Hayes. A scholar is included among the top collaborators of Fiona Hayes based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Fiona Hayes. Fiona Hayes is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | A Pattern Language for the Perception, Design and Implementation of Distributed Application Partitioning | 0 |
| 2 | Object-oriented development: the fusion method | 374 |
| 3 | 66 | |
| 4 | Formal Techniques for OO Software Development (Panel). | 1 |
| 5 | Lessons from Hewlett-Packard's experience of using object-oriented technology | 3 |
| 6 | 8 | |
| 7 | Criteria for Comparing Object-Oriented Development Methods | 2 |
| 8 | 42 | |
| 9 | 19 | |
| 10 | 3 |
About Fiona Hayes
Fiona Hayes is a scholar working on Software, Computational Theory and Mathematics and Artificial Intelligence, having authored 10 papers that have together received 518 indexed citations. Recurring topics across this work include Model-Driven Software Engineering Techniques (4 papers), Software Engineering Research (4 papers) and Logic, programming, and type systems (3 papers). The work is most often cited by research in Software (232 citations), Information Systems (297 citations) and Artificial Intelligence (350 citations). Fiona Hayes has collaborated with scholars based in United Kingdom, United States and Germany. Frequent co-authors include Derek Coleman, Patrick Arnold, Dennis de Champeaux, Pierre America, António Rito Silva, Roger Duke, Gary T. Leavens and Doug Lea. Their work appears in journals such as IEEE Transactions on Software Engineering and ACM SIGPLAN Notices.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.