Peter Hearty
Impact in
- Software top 2%
- Software Reliability and Analysis Research
- Software Testing and Debugging Techniques
- Information Systems top 2%
- Software Engineering Research
- Software Engineering Techniques and Practices
Papers in
- Software 7
- Software Reliability and Analysis Research 7
-
- Software Engineering Research 5
- Software Engineering Techniques and Practices 2
- Co-authors
- Norman Fenton (7 shared papers)Martin Neil (7 shared papers)David G. Márquez (3 shared papers)William Marsh (3 shared papers)Paul Krause (3 shared papers)Łukasz Radliński (2 shared papers)
- Journals
- Information and Software Technology (1 paper)Reliability Engineering & System Safety (1 paper)Empirical Software Engineering (1 paper)IEEE Transactions on Software Engineering (1 paper)View (1 paper)
- Partner nations
- United KingdomPolandMexico
In The Last Decade
Peter Hearty
7 papers receiving 373 citations
Peers
Comparison fields: 5 of 45
- Software 293
- Information Systems 293
- Statistics, Probability and Uncertainty 69
- Safety, Risk, Reliability and Quality 43
- Computer Networks and Communications 77
Countries citing papers authored by Peter Hearty
This map shows the geographic impact of Peter Hearty'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 Peter Hearty with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peter Hearty more than expected).
Fields of papers citing papers by Peter Hearty
This network shows the impact of papers produced by Peter Hearty. 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 Peter Hearty. The network helps show where Peter Hearty may publish in the future.
Co-authors
The 6 scholars most cited alongside Peter Hearty, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2006 | 132 | |
| 2 | 2008 | 93 | |
| 3 | 2008 | 53 | |
| 4 | 2006 | 52 | |
| 5 | 2007 | 50 | |
| 6 | 2007 | 30 | |
| 7 | 2005 | 3 |
About Peter Hearty
Peter Hearty is a scholar working on Software, Information Systems, Artificial Intelligence, Computer Networks and Communications and Statistics, Probability and Uncertainty, having authored 7 papers that have together received 413 indexed citations. Recurring topics across this work include Software Reliability and Analysis Research (7 papers), Software Engineering Research (5 papers), Bayesian Modeling and Causal Inference (3 papers), Risk and Safety Analysis (2 papers), Software System Performance and Reliability (2 papers) and Software Engineering Techniques and Practices (2 papers). The work is most often cited by research in Software (293 citations), Information Systems (293 citations), Statistics, Probability and Uncertainty (69 citations), Safety, Risk, Reliability and Quality (43 citations) and Computer Networks and Communications (77 citations). Peter Hearty has collaborated with scholars based in United Kingdom, Poland and Mexico. Frequent co-authors include Norman Fenton, Martin Neil, David G. Márquez, William Marsh, Paul Krause and Łukasz Radliński. Their work appears in journals such as Information and Software Technology, Reliability Engineering & System Safety, Empirical Software Engineering, IEEE Transactions on Software Engineering and View.
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.