Chris Ackermann

464 citations
15 papers · 148 · h-index 8

Impact in

  • Software top 10%
    • Software Reliability and Analysis Research
    • Software Testing and Debugging Techniques
    • Model-Driven Software Engineering Techniques
    • Software Engineering Research
    • Software Engineering Techniques and Practices

Papers in

    • Software Engineering Research 5
    • Software Engineering Techniques and Practices 3
    • Advanced Software Engineering Methodologies 3
    • Data Stream Mining Techniques 2
    • Anomaly Detection Techniques and Applications 2

Chris Ackermann

15 papers receiving 137 citations

Peers

Chris Ackermann
Comparison fields: 5 of 49
  • Software 51
  • Information Systems 57
  • Artificial Intelligence 57
  • Medical Laboratory Technology 2
  • Computational Theory and Mathematics 24
Replace Brian Monahan with:
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Carlos Luna Uruguay
Chengwei Liu China
Germán Vega France
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Mislav Balunović Switzerland
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Chris Ackermann relative to Brian Monahan United States Brian Monahan's profile →
Citations per field
00.5×
Brian Monahan · 1×
Citations per year

Countries citing papers authored by Chris Ackermann

Since Specialization
Citations

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

Fields of papers citing papers by Chris Ackermann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Chris Ackermann, 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 Chris Ackermann Line = papers co-authored together Chris Ackermann links everyone, so they are left out of the graph.

All Works

15 of 15 papers shown
#Work
1 201025
2 201423
3 200919
4 200518
5 200914
6 201410
7 20089
8 20079
9 20086
10 20094
11 20053
12 19933
13 19932
14 20022
15 20031

About Chris Ackermann

Chris Ackermann is a scholar working on Information Systems, Artificial Intelligence, Software, Statistics, Probability and Uncertainty and Management Information Systems, having authored 15 papers that have together received 148 indexed citations. Recurring topics across this work include Software Engineering Research (5 papers), Software Testing and Debugging Techniques (4 papers), Software Reliability and Analysis Research (3 papers), Advanced Software Engineering Methodologies (3 papers), Advanced Statistical Process Monitoring (3 papers), Software Engineering Techniques and Practices (3 papers), Data Stream Mining Techniques (2 papers) and Anomaly Detection Techniques and Applications (2 papers). The work is most often cited by research in Software (51 citations), Information Systems (57 citations), Artificial Intelligence (57 citations), Medical Laboratory Technology (2 citations) and Computational Theory and Mathematics (24 citations). Chris Ackermann has collaborated with scholars based in United States, Germany and Türkiye. Frequent co-authors include Arnab Ray, Rance Cleaveland, Charles Shelton, Mikael Lindvall, Samuel H. Huang, Dharmalingam Ganesan, Marvin V. Zelkowitz, Kristen Summers, Victor R. Basili and Lorin Hochstein. Their work appears in journals such as IEEE Transactions on Semiconductor Manufacturing, Big Data, Empirical Software Engineering, SAE technical papers on CD-ROM/SAE technical paper series and Innovations in Systems and 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.

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