Steve Versteeg
About
In The Last Decade
Steve Versteeg
28 papers receiving 1.4k citations
Hit Papers
Peers
Comparison fields: 5 of 56
- Computer Networks and Communications 1.1k
- Information Systems 1.0k
- Signal Processing 543
- Artificial Intelligence 314
- Software 190
Countries citing papers authored by Steve Versteeg
This map shows the geographic impact of Steve Versteeg'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 Steve Versteeg with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Steve Versteeg more than expected).
Fields of papers citing papers by Steve Versteeg
This network shows the impact of papers produced by Steve Versteeg. 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 Steve Versteeg. The network helps show where Steve Versteeg may publish in the future.
Co-authorship network of co-authors of Steve Versteeg
This figure shows the co-authorship network connecting the top 25 collaborators of Steve Versteeg. A scholar is included among the top collaborators of Steve Versteeg 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 Steve Versteeg. Steve Versteeg is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Title | Journal | Authors | Indexed citations |
|---|---|---|---|---|
| 1 | A positional keyword-based approach to inferring fine-grained message formats | Future Generation Computer Systems | Jiaojiao Jiang, Steve Versteeg et al. | 6 |
| 2 | P-Gram: Positional N-Gram for the Clustering of Machine-Generated Messages | IEEE Access | Jiaojiao Jiang, Steve Versteeg et al. | 6 |
| 3 | Mining accurate message formats for service APIs | Swinburne Research Bank (Swinburne University of Technology) | Steve Versteeg, Jun Han et al. | 9 |
| 4 | GHTraffic: A Dataset for Reproducible Research in Service-Oriented Computing | Lincoln University Research Archive (Lincoln University) | Jens Dietrich, Hans W. Guesgen et al. | 0 |
| 5 | Service virtualisation of internet-of-things devices: techniques and challenges | International Conference on Software Engineering | Steve Versteeg, Jun Han et al. | 6 |
| 6 | A Petri-Net-Based Virtual Deployment Testing Environment for Enterprise Software Systems | The Computer Journal | Jian Yu, Jun Han et al. | 1 |
| 7 | Formulating Cost-Effective Monitoring Strategies for Service-Based Systems | IEEE Transactions on Software Engineering | Qiang He, Jun Han et al. | 24 |
| 8 | Generating service models by trace subsequence substitution | Swinburne Research Bank (Swinburne University of Technology) | Miao Du, Jean-Guy Schneider et al. | 11 |
| 9 | SLA-Based Resource Provisioning for Hosted Software-as-a-Service Applications in Cloud Computing Environments | IEEE Transactions on Services Computing | Linlin Wu, Saurabh Garg et al. | 109 |
| 10 | Predicting bug-fixing time: An empirical study of commercial software projects | 2013 35th International Conference on Software Engineering (ICSE) | Hongyu Zhang, Liang Gong et al. | 100 |
| 11 | Classification of malware based on integrated static and dynamic features | Journal of Network and Computer Applications | Rafiqul Islam, Ronghua Tian et al. | 187 |
| 12 | A framework for ranking of cloud computing services breakdown → | Future Generation Computer Systems | Saurabh Garg, Steve Versteeg et al. | 610 |
| 13 | Probabilistic Critical Path Identification for Cost-Effective Monitoring of Service-Based Systems | Figshare | Qiang He, Jun Han et al. | 8 |
| 14 | Emulation of Cloud-Scale Environments for Scalability Testing | Swinburne Research Bank (Swinburne University of Technology) | Steve Versteeg, Jean-Guy Schneider et al. | 2 |
| 15 | Run-time management and optimization of web service monitoring systems | Swinburne Research Bank (Swinburne University of Technology) | Jun Han, Jean-Guy Schneider et al. | 2 |
| 16 | Classification of Malware Based on String and Function Feature Selection | Rafiqul Islam, Ronghua Tian et al. | 52 | |
| 17 | Modelling Enterprise System Protocols and Trace Conformance | Figshare | Jean-Guy Schneider, Jun Han et al. | 5 |
| 18 | An automated classification system based on the strings of trojan and virus families | Ronghua Tian, Lynn Batten et al. | 84 | |
| 19 | SOABSE: An approach to realizing business-oriented security requirements with Web Service security policies | Swinburne Research Bank (Swinburne University of Technology) | Jun Han, Ingo Mueller et al. | 1 |
| 20 | Function length as a tool for malware classification | Lynn Batten, Steve Versteeg et al. | 82 |
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.