Mark Gabel
Impact in
- Software top 0.5%
- Software Testing and Debugging Techniques
- Software Reliability and Analysis Research
- Information Systems top 0.5%
- Software Engineering Research
- Software Engineering Techniques and Practices
Papers in
-
- Software Engineering Research 12
- Software 12
- Software Testing and Debugging Techniques 12
- Software Reliability and Analysis Research 6
- Co-authors
- Zhendong Su (12 shared papers)Earl T. Barr (3 shared papers)Abram Hindle (3 shared papers)Prémkumar Dévanbu (3 shared papers)Lingxiao Jiang (1 shared paper)Moisés Goldszmidt (2 shared papers)Junfeng Yang (2 shared papers)Yuan Yu (1 shared paper)
- Journals
- ACM SIGPLAN Notices (1 paper)Communications of the ACM (1 paper)International Conference on Software Engineering (1 paper)
- Partner nations
- United StatesUnited KingdomCanada
In The Last Decade
Mark Gabel
12 papers receiving 1.4k citations
Mark Gabel's Hit Papers
Peers
Comparison fields: 5 of 45
- Software 876
- Information Systems 1.3k
- Signal Processing 447
- Computer Networks and Communications 351
- Artificial Intelligence 443
Countries citing papers authored by Mark Gabel
This map shows the geographic impact of Mark Gabel'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 Gabel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mark Gabel more than expected).
Fields of papers citing papers by Mark Gabel
This network shows the impact of papers produced by Mark Gabel. 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 Gabel. The network helps show where Mark Gabel may publish in the future.
Co-authors
The 9 scholars most cited alongside Mark Gabel, 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 | On the naturalness of software Hit paper breakdown → | 2012 | 337 |
| 2 | On the naturalness of software Hit paper breakdown → | 2012 | 287 |
| 3 | 2008 | 222 | |
| 4 | 2016 | 184 | |
| 5 | 2010 | 136 | |
| 6 | 2008 | 125 | |
| 7 | 2010 | 64 | |
| 8 | 2008 | 61 | |
| 9 | 2010 | 51 | |
| 10 | 2012 | 23 | |
| 11 | 2010 | 8 | |
| 12 | Inferring programmer intent and related errors from software | 2011 | 1 |
About Mark Gabel
Mark Gabel is a scholar working on Information Systems, Software, Artificial Intelligence, Computer Networks and Communications and Computational Theory and Mathematics, having authored 12 papers that have together received 1.5k indexed citations. Recurring topics across this work include Software Engineering Research (12 papers), Software Testing and Debugging Techniques (12 papers), Software Reliability and Analysis Research (6 papers), Natural Language Processing Techniques (1 paper), Logic, programming, and type systems (1 paper), Evolutionary Algorithms and Applications (1 paper), Formal Methods in Verification (1 paper) and Software System Performance and Reliability (1 paper). The work is most often cited by research in Software (876 citations), Information Systems (1.3k citations), Signal Processing (447 citations), Computer Networks and Communications (351 citations) and Artificial Intelligence (443 citations). Mark Gabel has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Zhendong Su, Earl T. Barr, Abram Hindle, Prémkumar Dévanbu, Lingxiao Jiang, Moisés Goldszmidt, Junfeng Yang, Yuan Yu and Yuan Yu. Their work appears in journals such as ACM SIGPLAN Notices, Communications of the ACM and International Conference on Software Engineering.
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.