Marc Eaddy
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
- Service-Oriented Architecture and Web Services
- Web Data Mining and Analysis
Papers in
-
- Software Engineering Research 6
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- Advanced Software Engineering Methodologies 5
- Co-authors
- Alfred V. Aho (7 shared papers)Gail C. Murphy (2 shared papers)Giuliano Antoniol (1 shared paper)Yann‐Gaël Guéhéneuc (1 shared paper)Thomas Zimmermann (1 shared paper)Nachiappan Nagappan (1 shared paper)Steven Feiner (2 shared papers)Jason S. Babcock (1 shared paper)
- Journals
- IEEE Transactions on Software Engineering (1 paper)Lecture notes in computer science (1 paper)Columbia Academic Commons (Columbia University) (2 papers)PolyPublie (École Polytechnique de Montréal) (1 paper)
- Partner nations
- United StatesCanada
In The Last Decade
Marc Eaddy
9 papers receiving 452 citations
Peers
Comparison fields: 5 of 28
- Software 237
- Information Systems 427
- Artificial Intelligence 245
- Computer Networks and Communications 133
- Human-Computer Interaction 31
Countries citing papers authored by Marc Eaddy
This map shows the geographic impact of Marc Eaddy'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 Marc Eaddy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marc Eaddy more than expected).
Fields of papers citing papers by Marc Eaddy
This network shows the impact of papers produced by Marc Eaddy. 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 Marc Eaddy. The network helps show where Marc Eaddy may publish in the future.
Co-authors
The 8 scholars most cited alongside Marc Eaddy, 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 | 2008 | 191 | |
| 2 | 2008 | 128 | |
| 3 | 2007 | 68 | |
| 4 | 2007 | 31 | |
| 5 | 2004 | 30 | |
| 6 | Statement Annotations for Fine-Grained Advising | 2006 | 18 |
| 7 | An empirical assessment of the crosscutting concern problem | 2008 | 8 |
| 8 | 2005 | 6 | |
| 9 | 2006 | 1 |
About Marc Eaddy
Marc Eaddy is a scholar working on Information Systems, Artificial Intelligence, Software, Computer Networks and Communications and Computer Vision and Pattern Recognition, having authored 9 papers that have together received 481 indexed citations. Recurring topics across this work include Software Engineering Research (6 papers), Advanced Software Engineering Methodologies (5 papers), Software Reliability and Analysis Research (4 papers), Software System Performance and Reliability (2 papers), Interactive and Immersive Displays (1 paper), Real-Time Systems Scheduling (1 paper), Software Testing and Debugging Techniques (1 paper) and Distributed systems and fault tolerance (1 paper). The work is most often cited by research in Software (237 citations), Information Systems (427 citations), Artificial Intelligence (245 citations), Computer Networks and Communications (133 citations) and Human-Computer Interaction (31 citations). Marc Eaddy has collaborated with scholars based in United States and Canada. Frequent co-authors include Alfred V. Aho, Gail C. Murphy, Giuliano Antoniol, Yann‐Gaël Guéhéneuc, Thomas Zimmermann, Nachiappan Nagappan, Steven Feiner and Jason S. Babcock. Their work appears in journals such as IEEE Transactions on Software Engineering, Lecture notes in computer science, Columbia Academic Commons (Columbia University) and PolyPublie (École Polytechnique de Montréal).
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.