Michael Reif

420 total citations
15 papers, 258 citations indexed

About

Michael Reif is a scholar working on Signal Processing, Information Systems and Artificial Intelligence. According to data from OpenAlex, Michael Reif has authored 15 papers receiving a total of 258 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Signal Processing, 11 papers in Information Systems and 7 papers in Artificial Intelligence. Recurrent topics in Michael Reif's work include Advanced Malware Detection Techniques (12 papers), Software Engineering Research (8 papers) and Software Testing and Debugging Techniques (5 papers). Michael Reif is often cited by papers focused on Advanced Malware Detection Techniques (12 papers), Software Engineering Research (8 papers) and Software Testing and Debugging Techniques (5 papers). Michael Reif collaborates with scholars based in Germany, Canada and Sweden. Michael Reif's co-authors include Mira Mezini, Michael Eichberg, Ben Hermann, Tom Lewis, Cuong N. N. Tran, Florian Göpfert, Felix Günther, Sarah Nadi, Daniel Demmler and Sven Amann and has published in prestigious journals such as Journal of Applied Polymer Science, Austral Ecology and TUbilio (Technical University of Darmstadt).

In The Last Decade

Michael Reif

15 papers receiving 252 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Michael Reif Germany 8 145 137 100 77 39 15 258
Jeff Kidd United States 6 12 0.1× 228 1.7× 163 1.6× 105 1.4× 22 0.6× 9 345
Naresh Kumar India 9 33 0.2× 69 0.5× 8 0.1× 72 0.9× 7 0.2× 59 256
He Ye Sweden 6 19 0.1× 129 0.9× 127 1.3× 58 0.8× 9 0.2× 12 245
Francisco Rocha Portugal 8 30 0.2× 156 1.1× 1 0.0× 116 1.5× 18 0.5× 12 274
Michael E. Schuckers United States 9 72 0.5× 57 0.4× 21 0.3× 9 0.2× 34 223
Luiz Cláudio Navarro Brazil 7 37 0.3× 30 0.2× 15 0.1× 16 0.2× 16 177
Cliff G. Martin United States 8 7 0.0× 25 0.2× 2 0.0× 21 0.3× 9 0.2× 25 338
K. Jairam Naik India 10 17 0.1× 52 0.4× 3 0.0× 41 0.5× 1 0.0× 42 283
Suhail Yousaf Pakistan 5 93 0.6× 208 1.5× 109 1.4× 6 0.2× 15 444

Countries citing papers authored by Michael Reif

Since Specialization
Citations

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

Fields of papers citing papers by Michael Reif

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael Reif

This figure shows the co-authorship network connecting the top 25 collaborators of Michael Reif. A scholar is included among the top collaborators of Michael Reif 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 Michael Reif. Michael Reif is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

15 of 15 papers shown
1.
Krüger, Stefan, Michael Reif, Sarah Nadi, et al.. (2023). Securing Your Crypto-API Usage Through Tool Support - A Usability Study. TUbilio (Technical University of Darmstadt). 14–25. 1 indexed citations
2.
Reif, Michael, et al.. (2021). CiFi: Versatile Analysis of Class and Field Immutability. TUbilio (Technical University of Darmstadt). 979–990. 1 indexed citations
3.
Reif, Michael, et al.. (2020). TACAI: an intermediate representation based on abstract interpretation. TUbilio (Technical University of Darmstadt). 2–7. 2 indexed citations
4.
Reif, Michael, et al.. (2019). Judge: identifying, understanding, and evaluating sources of unsoundness in call graphs. TUbilio (Technical University of Darmstadt). 251–261. 24 indexed citations
5.
Reif, Michael, et al.. (2019). A Dataset of Parametric Cryptographic Misuses. 96–100. 5 indexed citations
6.
Reif, Michael, et al.. (2018). Systematic evaluation of the unsoundness of call graph construction algorithms for Java. 107–112. 16 indexed citations
7.
Eichberg, Michael, et al.. (2018). A unified lattice model and framework for purity analyses. 340–350. 7 indexed citations
8.
Eichberg, Michael, et al.. (2018). Lattice based modularization of static analyses. 113–118. 5 indexed citations
9.
Krüger, Stefan, Sarah Nadi, Michael Reif, et al.. (2017). CogniCrypt: Supporting developers in using cryptography. TUbilio (Technical University of Darmstadt). 931–936. 58 indexed citations
10.
Reif, Michael, Michael Eichberg, Ben Hermann, & Mira Mezini. (2017). Hermes: assessment and creation of effective test corpora. 43–48. 8 indexed citations
11.
Amann, Sven, et al.. (2017). CodeMatch: obfuscation won't conceal your repackaged app. 638–648. 32 indexed citations
12.
Reif, Michael, et al.. (2016). Call graph construction for Java libraries. 474–486. 31 indexed citations
13.
Hermann, Ben, Michael Reif, Michael Eichberg, & Mira Mezini. (2015). Getting to know you: towards a capability model for Java. 758–769. 4 indexed citations
14.
15.
Sjöberg, John, et al.. (2009). Drug diffusion in neutral and ionic hydrogels assembled from acetylated galactoglucomannan. Journal of Applied Polymer Science. 112(4). 2401–2412. 24 indexed citations

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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