Daniel E. Krutz

438 citations
44 papers · 318 · h-index 11

Impact in

Papers in

    • Software Engineering Research 17
    • Digital and Cyber Forensics 8
    • Software Engineering Techniques and Practices 4
    • Advanced Malware Detection Techniques 13

Daniel E. Krutz

42 papers receiving 307 citations

Peers

Daniel E. Krutz
Comparison fields: 5 of 46
  • Software 107
  • Human Factors and Ergonomics 46
  • Signal Processing 132
  • Computer Science Applications 54
  • Information Systems 186
Replace Paige Rodeghero with:
Paige Rodeghero United States
Eman Abdullah AlOmar United States
Anthony Peruma United States
Stephanie Ludi United States
Yury Puzis United States
Christopher Douce United Kingdom
Carol V. Alexandru Switzerland
Sridhar Chimalakonda India
Alenka Kavčič Slovenia
Luke Church United Kingdom
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Citations per field
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Citations per year

Countries citing papers authored by Daniel E. Krutz

Since Specialization
Citations

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

Fields of papers citing papers by Daniel E. Krutz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel E. Krutz. 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 Daniel E. Krutz. The network helps show where Daniel E. Krutz may publish in the future.

Co-authors

The 24 scholars most cited alongside Daniel E. Krutz, 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 Daniel E. Krutz Line = papers co-authored together Daniel E. Krutz links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 44 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201434
2 201527
3 201325
4 202023
5 201418
6 201815
7 201814
8 201914
9 202013
10 201612
11 201712
12 201910
13 20178
14 20208
15 20187
16 20177
17 20206
18 20166
19 20196
20 20135

About Daniel E. Krutz

Daniel E. Krutz is a scholar working on Information Systems, Signal Processing, Software, Artificial Intelligence and Human Factors and Ergonomics, having authored 44 papers that have together received 318 indexed citations. Recurring topics across this work include Software Engineering Research (17 papers), Software Testing and Debugging Techniques (14 papers), Advanced Malware Detection Techniques (13 papers), Digital Accessibility for Disabilities (10 papers), Digital and Cyber Forensics (8 papers), Advanced Software Engineering Methodologies (5 papers), Software Engineering Techniques and Practices (4 papers) and Teaching and Learning Programming (4 papers). The work is most often cited by research in Software (107 citations), Human Factors and Ergonomics (46 citations), Signal Processing (132 citations), Computer Science Applications (54 citations) and Information Systems (186 citations). Daniel E. Krutz has collaborated with scholars based in United States, Italy and Netherlands. Frequent co-authors include Anthony Peruma, Emad Shihab, Yasmine N. Elglaly, Qi Yu, Mohamed Wiem Mkaouer, Wei Le, Nuthan Munaiah, Travis Desell, J. Scott Hawker and Andrew Meneely. Their work appears in journals such as ACM Transactions on Software Engineering and Methodology, Machine Learning, ACM Inroads, Lecture notes in computer science and Proceedings of the Genetic and Evolutionary Computation Conference.

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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