Mark C. Chu-Carroll
- Information Systems top 1%
- Software top 2%
- Artificial Intelligence top 5%
- Computer Networks and Communications top 5%
- Computer Science Applications top 5%
- Co-authors
- Annie T. T. YingGail C. MurphyRaymond T. NgJames L. WrightSara SprenkleDavid ShieldsJeffrey PalmLori Pollock
- Topics
- Advanced Software Engineering Methodologies (8 papers)Software Engineering Research (8 papers)Software System Performance and Reliability (5 papers)
- Journals
- IEEE Transactions on Software EngineeringACM SIGSOFT Software Engineering Notes
- Partner nations
- United StatesCanada
In The Last Decade
Mark C. Chu-Carroll
11 papers receiving 507 citations
Hit Papers
Peers
Comparison fields: 5 of 31
- Information Systems 510
- Software 273
- Artificial Intelligence 228
- Computer Networks and Communications 201
- Computer Science Applications 65
Countries citing papers authored by Mark C. Chu-Carroll
This map shows the geographic impact of Mark C. Chu-Carroll'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 Mark C. Chu-Carroll with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mark C. Chu-Carroll more than expected).
Fields of papers citing papers by Mark C. Chu-Carroll
This network shows the impact of papers produced by Mark C. Chu-Carroll. 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 Mark C. Chu-Carroll. The network helps show where Mark C. Chu-Carroll may publish in the future.
Co-authorship network of co-authors of Mark C. Chu-Carroll
This figure shows the co-authorship network connecting the top 25 collaborators of Mark C. Chu-Carroll. A scholar is included among the top collaborators of Mark C. Chu-Carroll 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 Mark C. Chu-Carroll. Mark C. Chu-Carroll is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Good Math: A Geek's Guide to the Beauty of Numbers, Logic, and Computation | 3 |
| 2 | Code in the Cloud | 2 |
| 3 | The Mockingbird System: A Compiler-based Approach to Maximally Interoperable Distributed Programming | 0 |
| 4 | 29 | |
| 5 | Predicting source code changes by mining change historybreakdown → | 407 |
| 6 | 6 | |
| 7 | 23 | |
| 8 | 1 | |
| 9 | 32 | |
| 10 | 2 | |
| 11 | 28 | |
| 12 | Software Configuration Management as a Mechanism for Multidimensional Separation of Concerns | 2 |
| 13 | 5 |
About Mark C. Chu-Carroll
Mark C. Chu-Carroll is a scholar working on Software, Information Systems and Artificial Intelligence, having authored 13 papers that have together received 540 indexed citations. Recurring topics across this work include Advanced Software Engineering Methodologies (8 papers), Software Engineering Research (8 papers) and Software System Performance and Reliability (5 papers). The work is most often cited by research in Software (273 citations), Information Systems (510 citations) and Computer Science Applications (65 citations). Mark C. Chu-Carroll has collaborated with scholars based in United States and Canada. Frequent co-authors include Annie T. T. Ying, Gail C. Murphy, Raymond T. Ng, James L. Wright, Sara Sprenkle, David Shields, Jeffrey Palm, Lori Pollock, David Shepherd and Christopher Barton. Their work appears in journals such as IEEE Transactions on Software Engineering and ACM SIGSOFT Software Engineering Notes.
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.