Shane McIntosh

6.0k total citations · 6 hit papers
111 papers, 4.4k citations indexed

About

Shane McIntosh is a scholar working on Information Systems, Software and Computer Networks and Communications. According to data from OpenAlex, Shane McIntosh has authored 111 papers receiving a total of 4.4k indexed citations (citations by other indexed papers that have themselves been cited), including 105 papers in Information Systems, 58 papers in Software and 30 papers in Computer Networks and Communications. Recurrent topics in Shane McIntosh's work include Software Engineering Research (104 papers), Software Reliability and Analysis Research (48 papers) and Software Engineering Techniques and Practices (38 papers). Shane McIntosh is often cited by papers focused on Software Engineering Research (104 papers), Software Reliability and Analysis Research (48 papers) and Software Engineering Techniques and Practices (38 papers). Shane McIntosh collaborates with scholars based in Canada, Japan and United States. Shane McIntosh's co-authors include Ahmed E. Hassan, Yasutaka Kamei, Kenichi Matsumoto, Chakkrit Tantithamthavorn, Bram Adams, Naoyasu Ubayashi, Kazuhiro Yamashita, Patanamon Thongtanunam, Hajimu Iida and Martin Pinzger and has published in prestigious journals such as IEEE Transactions on Software Engineering, IEEE Software and Empirical Software Engineering.

In The Last Decade

Shane McIntosh

101 papers receiving 4.3k citations

Hit Papers

An Empirical Comparison of Model Validation Techniques fo... 2014 2026 2018 2022 2016 2018 2016 2015 2014 100 200 300 400
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. An Empirical Comparison of Model Validation Techniques for Defect Prediction Models
    2016 430 citations Shane McIntosh, Ahmed E. Hassan et al. IEEE Transactions on Software Engineering profile →
  2. The Impact of Automated Parameter Optimization on Defect Prediction Models
    2018 291 citations Shane McIntosh, Ahmed E. Hassan et al. IEEE Transactions on Software Engineering profile →
  3. Automated parameter optimization of classification techniques for defect prediction models
    2016 253 citations Shane McIntosh, Ahmed E. Hassan et al. profile →
  4. Revisiting the Impact of Classification Techniques on the Performance of Defect Prediction Models
    2015 249 citations Shane McIntosh, Ahmed E. Hassan et al. profile →
  5. The impact of code review coverage and code review participation on software quality: a case study of the qt, VTK, and ITK projects
    2014 242 citations Shane McIntosh, Yasutaka Kamei et al. PolyPublie (École Polytechnique de Montréal) profile →
  6. An empirical study of the impact of modern code review practices on software quality
    2015 219 citations Shane McIntosh, Yasutaka Kamei et al. Empirical Software Engineering profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shane McIntosh Canada 32 4.0k 2.5k 1.3k 786 659 111 4.4k
Yasutaka Kamei Japan 27 3.1k 0.8× 2.2k 0.8× 968 0.7× 620 0.8× 470 0.7× 126 3.5k
Sunghun Kim Hong Kong 30 4.3k 1.1× 3.1k 1.2× 1.3k 1.0× 1.1k 1.4× 402 0.6× 75 5.0k
Foutse Khomh Canada 37 4.1k 1.0× 2.4k 1.0× 1.5k 1.1× 1.3k 1.6× 601 0.9× 248 5.1k
Romain Robbes Chile 31 2.9k 0.7× 1.5k 0.6× 921 0.7× 989 1.3× 517 0.8× 98 3.3k
Tom Mens Belgium 34 4.1k 1.0× 2.2k 0.9× 1.2k 0.9× 2.2k 2.8× 656 1.0× 173 4.9k
Chakkrit Tantithamthavorn Australia 29 2.6k 0.7× 1.9k 0.7× 908 0.7× 762 1.0× 224 0.3× 88 3.3k
Michael W. Godfrey Canada 33 3.3k 0.8× 1.6k 0.6× 936 0.7× 975 1.2× 757 1.1× 141 3.7k
E. James Whitehead United States 25 2.9k 0.7× 1.9k 0.7× 1.2k 0.9× 906 1.2× 238 0.4× 66 3.3k
Earl T. Barr United Kingdom 23 2.5k 0.6× 2.0k 0.8× 763 0.6× 985 1.3× 216 0.3× 71 3.4k
Baishakhi Ray United States 26 1.9k 0.5× 1.4k 0.5× 776 0.6× 1.4k 1.8× 329 0.5× 81 3.6k

Countries citing papers authored by Shane McIntosh

Since Specialization
Citations

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

Fields of papers citing papers by Shane McIntosh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shane McIntosh

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

All Works

20 of 20 papers shown
1.
Dyer, Robert, et al.. (2025). WIA-SZZ: Work item aware SZZ. Empirical Software Engineering. 30(3).
2.
Chakraborty, Partha, et al.. (2024). Revisiting the Performance of Deep Learning-Based Vulnerability Detection on Realistic Datasets. IEEE Transactions on Software Engineering. 50(8). 2163–2177. 2 indexed citations
3.
4.
Xiao, Tao, et al.. (2024). A Mutation-Guided Assessment of Acceleration Approaches for Continuous Integration: An Empirical Study of YourBase. PolyPublie (École Polytechnique de Montréal). 556–568. 1 indexed citations
5.
McIntosh, Shane, et al.. (2024). Characterizing the Prevalence, Distribution, and Duration of Stale Reviewer Recommendations. IEEE Transactions on Software Engineering. 50(8). 2096–2109. 1 indexed citations
6.
Xiao, Tao, et al.. (2024). Quantifying and characterizing clones of self-admitted technical debt in build systems. Empirical Software Engineering. 29(2).
7.
Godfrey, Michael W., et al.. (2024). Reevaluating the Defect Proneness of Atoms of Confusion in Java Systems. 154–164.
8.
9.
McIntosh, Shane, et al.. (2024). Understanding the Implications of Changes to Build Systems. 1421–1433.
10.
McIntosh, Shane, et al.. (2024). Dependency-Induced Waste in Continuous Integration: An Empirical Study of Unused Dependencies in the npm Ecosystem. Proceedings of the ACM on software engineering.. 1(FSE). 2632–2655. 2 indexed citations
11.
12.
McIntosh, Shane, et al.. (2023). An empirical comparison of ethnic and gender diversity of DevOps and non-DevOps contributions to open-source projects. Empirical Software Engineering. 28(6). 4 indexed citations
13.
Li, Li, et al.. (2023). Understanding the quality and evolution of Android app build systems. Journal of Software Evolution and Process. 36(5). 1 indexed citations
14.
Dávid, István, et al.. (2022). Code Cloning in Smart Contracts on the Ethereum Platform: An Extended Replication Study. IEEE Transactions on Software Engineering. 49(4). 2006–2019. 17 indexed citations
15.
McIntosh, Shane, et al.. (2022). Exploring the Notion of Risk in Code Reviewer Recommendation. PolyPublie (École Polytechnique de Montréal). 139–150. 2 indexed citations
16.
Xiao, Tao, Shane McIntosh, Hideaki Hata, et al.. (2021). Characterizing and Mitigating Self-Admitted Technical Debt in Build Systems. IEEE Transactions on Software Engineering. 48(10). 4214–4228. 14 indexed citations
17.
Chen, Boqi, et al.. (2021). An Empirical Study of Type-Related Defects in Python Projects. IEEE Transactions on Software Engineering. 48(8). 3145–3158. 12 indexed citations
18.
Mussbacher, Gunter, et al.. (2021). Is Historical Data an Appropriate Benchmark for Reviewer Recommendation Systems? : A Case Study of the Gerrit Community. PolyPublie (École Polytechnique de Montréal). 30–41. 17 indexed citations
19.
McIntosh, Shane, et al.. (2018). Revisiting "Programmers' Build Errors" in the Visual Studio Context. 1 indexed citations
20.
Thongtanunam, Patanamon, Shane McIntosh, Ahmed E. Hassan, & Hajimu Iida. (2015). Investigating Code Review Practices in Defective Files: An Empirical Study of the Qt System. 168–179. 61 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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