David Shepherd

3.2k citations
134 papers · 2.1k · h-index 27

Impact in

Papers in

David Shepherd

121 papers receiving 2.0k citations

Peers

David Shepherd
Comparison fields: 5 of 162
  • Software 336
  • Computer Science Applications 296
  • Information Systems 896
  • Human-Computer Interaction 141
  • Artificial Intelligence 425
Replace Craig Larman with:
Craig Larman United States
Πάνος Λουρίδας Greece
Martin Schader Germany
Frederick W. B. Li United Kingdom
Robert M. Bell United States
Tommi Mikkonen Finland
Edward Yourdon United States
Damian A. Tamburri Netherlands
Brooks United Kingdom
Douglas Fisher United States
David Shepherd relative to Craig Larman United States Craig Larman's profile →
Citations per field
00.5×
Craig Larman · 1×
Citations per year

Countries citing papers authored by David Shepherd

Since Specialization
Citations

This map shows the geographic impact of David Shepherd'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 David Shepherd with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Shepherd more than expected).

Fields of papers citing papers by David Shepherd

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David Shepherd. 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 David Shepherd. The network helps show where David Shepherd may publish in the future.

Co-authors

The 25 scholars most cited alongside David Shepherd, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with David Shepherd Line = papers co-authored together David Shepherd links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 134 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1999166
2 2007161
3 1997117
4 2016105
5 201761
6 201555
7 201752
8 202051
9 201750
10 201950
11 198749
12 202047
13 200144
14
Design and Evaluation of an Automated Aspect Mining Tool
200443
15 201843
16 201439
17 201838
18 201238
19 201937
20 200635

About David Shepherd

David Shepherd is a scholar working on Information Systems, Computer Science Applications, Artificial Intelligence, Economics and Econometrics and Software, having authored 134 papers that have together received 2.1k indexed citations. Recurring topics across this work include Software Engineering Research (40 papers), Software Engineering Techniques and Practices (23 papers), Teaching and Learning Programming (19 papers), Open Source Software Innovations (15 papers), Advanced Software Engineering Methodologies (12 papers), Software Reliability and Analysis Research (10 papers), Monetary Policy and Economic Impact (10 papers) and Hearing Loss and Rehabilitation (10 papers). The work is most often cited by research in Software (336 citations), Computer Science Applications (296 citations), Information Systems (896 citations), Human-Computer Interaction (141 citations) and Artificial Intelligence (425 citations). David Shepherd has collaborated with scholars based in United States, United Kingdom and Switzerland. Frequent co-authors include Lori Pollock, K. Vijay‐Shanker, Thomas Fritz, Emily Hill, Robert Dixon, Zachary P. Fry, Norbert F. Voelkel, Kostadin Damevski, Rubin M. Tuder and Patrick Francis. Their work appears in journals such as IEEE Transactions on Software Engineering, Regional Studies, Journal of Systems and Software, Empirical Software Engineering and CHEST Journal.

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.

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