Danielle Azar
Impact in
- Software top 5%
- Software Reliability and Analysis Research
- Software Testing and Debugging Techniques
- Information Systems top 5%
- Software Engineering Research
- Software Engineering Techniques and Practices
Papers in
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- Software Engineering Research 10
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- AI in cancer detection 3
- Advanced Software Engineering Methodologies 2
- Co-authors
- Mark W. Wiggins (2 shared papers)Thomas Loveday (2 shared papers)Haidar Harmanani (6 shared papers)David G. Newman (1 shared paper)Frank Y. Shih (1 shared paper)Abdulkader Helwan (3 shared papers)Omar Falou (3 shared papers)Sima Tokajian (1 shared paper)
In The Last Decade
Danielle Azar
32 papers receiving 361 citations
Peers
Comparison fields: 5 of 99
- Software 86
- Information Systems 117
- Artificial Intelligence 101
- Industrial and Manufacturing Engineering 28
- Computer Networks and Communications 51
Countries citing papers authored by Danielle Azar
This map shows the geographic impact of Danielle Azar'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 Danielle Azar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Danielle Azar more than expected).
Fields of papers citing papers by Danielle Azar
This network shows the impact of papers produced by Danielle Azar. 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 Danielle Azar. The network helps show where Danielle Azar may publish in the future.
Co-authors
The 25 scholars most cited alongside Danielle Azar, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2010 | 47 | |
| 2 | 2014 | 45 | |
| 3 | 2016 | 29 | |
| 4 | 2021 | 24 | |
| 5 | Software Systems | 2008 | 23 |
| 6 | 2009 | 20 | |
| 7 | 2017 | 20 | |
| 8 | A Combined Ant Colony Optimization and Simulated Annealing Algorithm to Assess Stability and Fault-Proneness of Classes Based on Internal Software Quality Attributes | 2016 | 16 |
| 9 | 2018 | 16 | |
| 10 | 2020 | 14 | |
| 11 | 2002 | 14 | |
| 12 | 2018 | 13 | |
| 13 | A Comparative Study of Nine Machine Learning Techniques Used for the Prediction of Diseases | 2018 | 13 |
| 14 | 2018 | 10 | |
| 15 | 2010 | 9 | |
| 16 | 2018 | 9 | |
| 17 | 2022 | 9 | |
| 18 | 2023 | 8 | |
| 19 | 2022 | 7 | |
| 20 | 2023 | 7 |
About Danielle Azar
Danielle Azar is a scholar working on Information Systems, Artificial Intelligence, Software, Computer Networks and Communications and Molecular Biology, having authored 32 papers that have together received 382 indexed citations. Recurring topics across this work include Software Engineering Research (10 papers), Software Reliability and Analysis Research (9 papers), Software Testing and Debugging Techniques (5 papers), Software System Performance and Reliability (4 papers), AI in cancer detection (3 papers), Cutaneous Melanoma Detection and Management (2 papers), Advanced Software Engineering Methodologies (2 papers) and Vehicle Routing Optimization Methods (2 papers). The work is most often cited by research in Software (86 citations), Information Systems (117 citations), Artificial Intelligence (101 citations), Industrial and Manufacturing Engineering (28 citations) and Computer Networks and Communications (51 citations). Danielle Azar has collaborated with scholars based in Lebanon, Canada and Australia. Frequent co-authors include Mark W. Wiggins, Thomas Loveday, Haidar Harmanani, David G. Newman, Frank Y. Shih, Abdulkader Helwan, Omar Falou, Sima Tokajian, Azzam Mourad and Salah Bouktif. Their work appears in journals such as Information and Software Technology, Journal of Systems and Software, Safety Science, Physiological Measurement and Journal of X-Ray Science and Technology.
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.