Will Hayes
Impact in
- Software top 5%
- Software Reliability and Analysis Research
Papers in
- Co-authors
- James D. Herbsleb (1 shared paper)Mark C. Paulk (1 shared paper)David Zubrow (1 shared paper)Dennis R. Goldenson (1 shared paper)Kenneth A. Stacey (2 shared papers)James Dewey Watson (1 shared paper)Suzanne M. Miller (1 shared paper)JOHN H. BRADBURY (1 shared paper)
- Journals
- Nature (2 papers)Genetics Research (2 papers)British Medical Bulletin (1 paper)IEEE Software (1 paper)Novartis Foundation symposium (1 paper)
- Partner nations
- United KingdomUnited StatesGermany
In The Last Decade
Will Hayes
25 papers receiving 732 citations
Peers
Comparison fields: 5 of 105
- Software 83
- Management Information Systems 150
- Information Systems 321
- Endocrinology 57
- Molecular Medicine 46
Countries citing papers authored by Will Hayes
This map shows the geographic impact of Will 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 Will Hayes with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Will Hayes more than expected).
Fields of papers citing papers by Will Hayes
This network shows the impact of papers produced by Will 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 Will Hayes. The network helps show where Will Hayes may publish in the future.
Co-authors
The 13 scholars most cited alongside Will Hayes, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 1997 | 310 | |
| 2 | 1953 | 143 | |
| 3 | 1957 | 82 | |
| 4 | 1952 | 72 | |
| 5 | 2003 | 61 | |
| 6 | 1972 | 38 | |
| 7 | 1952 | 32 | |
| 8 | 1969 | 27 | |
| 9 | 2000 | 23 | |
| 10 | 1961 | 22 | |
| 11 | 1961 | 18 | |
| 12 | 1953 | 13 | |
| 13 | 1962 | 11 | |
| 14 | 1966 | 8 | |
| 15 | 2005 | 8 | |
| 16 | 2002 | 6 | |
| 17 | 2014 | 5 | |
| 18 | 1969 | 4 | |
| 19 | Physician induced and patient induced utilization of early cancer detection practices among black Americans. | 1989 | 3 |
| 20 | Cmmi® scampism distilled: appraisals for process improvement | 2005 | 3 |
About Will Hayes
Will Hayes is a scholar working on Software, Genetics, Information Systems, Safety, Risk, Reliability and Quality and Molecular Biology, having authored 25 papers that have together received 897 indexed citations. Recurring topics across this work include Bacterial Genetics and Biotechnology (7 papers), Software Reliability and Analysis Research (6 papers), Software Engineering Techniques and Practices (5 papers), Evolution and Genetic Dynamics (4 papers), Software Engineering Research (4 papers), Escherichia coli research studies (2 papers), Software Testing and Debugging Techniques (2 papers) and Technology Assessment and Management (2 papers). The work is most often cited by research in Software (83 citations), Management Information Systems (150 citations), Information Systems (321 citations), Endocrinology (57 citations) and Molecular Medicine (46 citations). Will Hayes has collaborated with scholars based in United Kingdom, United States and Germany. Frequent co-authors include James D. Herbsleb, Mark C. Paulk, David Zubrow, Dennis R. Goldenson, Kenneth A. Stacey, James Dewey Watson, Suzanne M. Miller, JOHN H. BRADBURY, Jim Armstrong and Justin Smith. Their work appears in journals such as Nature, Genetics Research, British Medical Bulletin, IEEE Software and Novartis Foundation symposium.
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.