Yaniv David
Impact in
- Software top 2%
- Software Testing and Debugging Techniques
- Software Reliability and Analysis Research
- Signal Processing top 2%
- Advanced Malware Detection Techniques
Papers in
- Software 10
- Software Testing and Debugging Techniques 10
- Software Reliability and Analysis Research 1
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- Software Engineering Research 9
- Co-authors
- Eran Yahav (10 shared papers)Nimrod Partush (6 shared papers)Uri Alon (2 shared papers)Nathaniel P. Katz (1 shared paper)Elizabeth Amir (1 shared paper)Dongdong She (1 shared paper)Baishakhi Ray (1 shared paper)Junfeng Yang (1 shared paper)
- Journals
- ACM SIGPLAN Notices (4 papers)Proceedings of the ACM on Programming Languages (1 paper)Polymers for Advanced Technologies (1 paper)arXiv (Cornell University) (1 paper)
- Partner nations
- IsraelUnited States
In The Last Decade
Yaniv David
12 papers receiving 500 citations
Peers
Comparison fields: 5 of 28
- Software 269
- Signal Processing 380
- Information Systems 387
- Artificial Intelligence 183
- Hardware and Architecture 31
Countries citing papers authored by Yaniv David
This map shows the geographic impact of Yaniv David'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 Yaniv David with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yaniv David more than expected).
Fields of papers citing papers by Yaniv David
This network shows the impact of papers produced by Yaniv David. 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 Yaniv David. The network helps show where Yaniv David may publish in the future.
Co-authors
The 9 scholars most cited alongside Yaniv David, 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 | 2014 | 92 | |
| 2 | 2016 | 79 | |
| 3 | 2017 | 65 | |
| 4 | 2014 | 63 | |
| 5 | 2020 | 50 | |
| 6 | 2018 | 50 | |
| 7 | 2016 | 49 | |
| 8 | 2018 | 42 | |
| 9 | 2016 | 15 | |
| 10 | 2017 | 12 | |
| 11 | Neural Reverse Engineering of Stripped Binaries | 2019 | 4 |
| 12 | 2022 | 4 |
About Yaniv David
Yaniv David is a scholar working on Software, Information Systems, Signal Processing, Artificial Intelligence and Hardware and Architecture, having authored 12 papers that have together received 525 indexed citations. Recurring topics across this work include Software Testing and Debugging Techniques (10 papers), Software Engineering Research (9 papers), Advanced Malware Detection Techniques (9 papers), Security and Verification in Computing (3 papers), Software Reliability and Analysis Research (1 paper), Organic Electronics and Photovoltaics (1 paper), Parallel Computing and Optimization Techniques (1 paper) and Conducting polymers and applications (1 paper). The work is most often cited by research in Software (269 citations), Signal Processing (380 citations), Information Systems (387 citations), Artificial Intelligence (183 citations) and Hardware and Architecture (31 citations). Yaniv David has collaborated with scholars based in Israel and United States. Frequent co-authors include Eran Yahav, Nimrod Partush, Uri Alon, Nathaniel P. Katz, Elizabeth Amir, Dongdong She, Baishakhi Ray, Junfeng Yang and Suman Jana. Their work appears in journals such as ACM SIGPLAN Notices, Proceedings of the ACM on Programming Languages, Polymers for Advanced Technologies and arXiv (Cornell University).
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.