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ORCIDShane McIntosh
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- affiliation: McGill University, Montreal, Canada
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2020 – today
- 2024
[j40]Wenhan Zhu
, Sebastian Proksch, Daniel M. Germán, Michael W. Godfrey, Li Li, Shane McIntosh:
What is an app store? The software engineering perspective. Empir. Softw. Eng. 29(1): 35 (2024)- [j39]Xueyao Yu, Filipe R. Cogo, Shane McIntosh, Michael W. Godfrey:
Studying the impact of risk assessment analytics on risk awareness and code review performance. Empir. Softw. Eng. 29(2): 46 (2024) - [j38]Tao Xiao, Zhili Zeng, Dong Wang, Hideaki Hata, Shane McIntosh, Kenichi Matsumoto:
Quantifying and characterizing clones of self-admitted technical debt in build systems. Empir. Softw. Eng. 29(2): 54 (2024) - [j37]Gengyi Sun, Sarra Habchi, Shane McIntosh:
RavenBuild: Context, Relevance, and Dependency Aware Build Outcome Prediction. Proc. ACM Softw. Eng. 1(FSE): 996-1018 (2024) - [j36]Nimmi Rashinika Weeraddana, Mahmoud Alfadel, Shane McIntosh:
Dependency-Induced Waste in Continuous Integration: An Empirical Study of Unused Dependencies in the npm Ecosystem. Proc. ACM Softw. Eng. 1(FSE): 2632-2655 (2024) - [j35]Pei Liu, Li Li, Kui Liu, Shane McIntosh, John C. Grundy:
Understanding the quality and evolution of Android app build systems. J. Softw. Evol. Process. 36(5) (2024) - [j34]Nimmi Rashinika Weeraddana, Mahmoud Alfadel, Shane McIntosh:
Characterizing Timeout Builds in Continuous Integration. IEEE Trans. Software Eng. 50(6): 1450-1463 (2024) - [j33]Farshad Kazemi, Maxime Lamothe, Shane McIntosh:
Characterizing the Prevalence, Distribution, and Duration of Stale Reviewer Recommendations. IEEE Trans. Software Eng. 50(8): 2096-2109 (2024) - [j32]Partha Chakraborty, Krishna Kanth Arumugam, Mahmoud Alfadel, Meiyappan Nagappan, Shane McIntosh:
Revisiting the Performance of Deep Learning-Based Vulnerability Detection on Realistic Datasets. IEEE Trans. Software Eng. 50(8): 2163-2177 (2024) - [j31]Xiaoyan Xu, Filipe R. Cogo, Shane McIntosh:
Mitigating the Uncertainty and Imprecision of Log-Based Code Coverage Without Requiring Additional Logging Statements. IEEE Trans. Software Eng. 50(9): 2350-2362 (2024) - [c63]Gengyi Sun, Mehran Meidani, Sarra Habchi, Mathieu Nayrolles, Shane McIntosh:
Code Impact Beyond Disciplinary Boundaries: Constructing a Multidisciplinary Dependency Graph and Analyzing Cross-Boundary Impact. ICSE-SEIP 2024: 122-133 - [c62]Mahmoud Alfadel, Shane McIntosh:
The Classics Never Go Out of Style: An Empirical Study of Downgrades from the Bazel Build Technology. ICSE 2024: 233:1-233:12 - [c61]Shane McIntosh:
Mining Our Way Back to Incremental Builds for DevOps Pipelines. MSR 2024: 48-49 - [c60]Zhili Zeng, Tao Xiao, Maxime Lamothe, Hideaki Hata, Shane McIntosh:
A Mutation-Guided Assessment of Acceleration Approaches for Continuous Integration: An Empirical Study of YourBase. MSR 2024: 556-568 - [c59]Issei Morita, Yutaro Kashiwa, Masanari Kondo, Jeongju Sohn, Shane McIntosh, Yasutaka Kamei, Naoyasu Ubayashi:
TraceJIT: Evaluating the Impact of Behavioral Code Change on Just-In-Time Defect Prediction. SANER 2024: 580-591 - [i14]Noble Saji Mathews, Yelizaveta Brus, Yousra Aafer, Meiyappan Nagappan, Shane McIntosh:
LLbezpeky: Leveraging Large Language Models for Vulnerability Detection. CoRR abs/2401.01269 (2024) - [i13]Wenhan Zhu, Sebastian Proksch, Daniel M. Germán, Michael W. Godfrey, Li Li, Shane McIntosh:
What Is an App Store? The Software Engineering Perspective. CoRR abs/2401.04287 (2024) - [i12]Tao Xiao, Zhili Zeng, Dong Wang, Hideaki Hata, Shane McIntosh, Kenichi Matsumoto:
Quantifying and Characterizing Clones of Self-Admitted Technical Debt in Build Systems. CoRR abs/2402.08920 (2024) - [i11]Partha Chakraborty, Krishna Kanth Arumugam, Mahmoud Alfadel, Meiyappan Nagappan, Shane McIntosh:
Revisiting the Performance of Deep Learning-Based Vulnerability Detection on Realistic Datasets. CoRR abs/2407.03093 (2024) - 2023
- [j30]Mehran Meidani, Maxime Lamothe, Shane McIntosh:
Assessing the exposure of software changes. Empir. Softw. Eng. 28(2): 41 (2023) - [j29]Nimmi Rashinika Weeraddana, Xiaoyan Xu, Mahmoud Alfadel, Shane McIntosh, Meiyappan Nagappan:
An empirical comparison of ethnic and gender diversity of DevOps and non-DevOps contributions to open-source projects. Empir. Softw. Eng. 28(6): 150 (2023) - [j28]Faizan Khan, Istvan David, Dániel Varró, Shane McIntosh:
Code Cloning in Smart Contracts on the Ethereum Platform: An Extended Replication Study. IEEE Trans. Software Eng. 49(4): 2006-2019 (2023) - [c58]Mahtab Nejati, Mahmoud Alfadel, Shane McIntosh:
Code Review of Build System Specifications: Prevalence, Purposes, Patterns, and Perceptions. ICSE 2023: 1213-1224 - [c57]Rungroj Maipradit, Dong Wang, Patanamon Thongtanunam, Raula Gaikovina Kula, Yasutaka Kamei, Shane McIntosh:
Repeated Builds During Code Review: An Empirical Study of the OpenStack Community. ASE 2023: 153-165 - [e4]Shane McIntosh, Eunjong Choi, Steffen Herbold:
Proceedings of the 19th International Conference on Predictive Models and Data Analytics in Software Engineering, PROMISE 2023, San Francisco, CA, USA, 8 December 2023. ACM 2023 [contents] - [i10]Rungroj Maipradit, Dong Wang, Patanamon Thongtanunam, Raula Gaikovina Kula, Yasutaka Kamei, Shane McIntosh:
Repeated Builds During Code Review: An Empirical Study of the OpenStack Community. CoRR abs/2308.10078 (2023) - 2022
- [j27]Toshiki Hirao, Shane McIntosh, Akinori Ihara, Kenichi Matsumoto:
Code Reviews With Divergent Review Scores: An Empirical Study of the OpenStack and Qt Communities. IEEE Trans. Software Eng. 48(2): 69-81 (2022) - [j26]Shivashree Vysali, Shane McIntosh, Bram Adams:
Quantifying, Characterizing, and Mitigating Flakily Covered Program Elements. IEEE Trans. Software Eng. 48(3): 1018-1029 (2022) - [j25]Keheliya Gallaba, John Ewart, Yves Junqueira, Shane McIntosh:
Accelerating Continuous Integration by Caching Environments and Inferring Dependencies. IEEE Trans. Software Eng. 48(6): 2040-2052 (2022) - [j24]Faizan Khan, Boqi Chen, Dániel Varró, Shane McIntosh:
An Empirical Study of Type-Related Defects in Python Projects. IEEE Trans. Software Eng. 48(8): 3145-3158 (2022) - [j23]Christophe Rezk, Yasutaka Kamei, Shane McIntosh:
The Ghost Commit Problem When Identifying Fix-Inducing Changes: An Empirical Study of Apache Projects. IEEE Trans. Software Eng. 48(9): 3297-3309 (2022) - [j22]Tao Xiao, Dong Wang, Shane McIntosh, Hideaki Hata, Raula Gaikovina Kula, Takashi Ishio, Kenichi Matsumoto:
Characterizing and Mitigating Self-Admitted Technical Debt in Build Systems. IEEE Trans. Software Eng. 48(10): 4214-4228 (2022) - [c56]Ruiyin Wen, Maxime Lamothe, Shane McIntosh:
How Does Code Reviewing Feedback Evolve?: A Longitudinal Study at Dell EMC. ICSE (SEIP) 2022: 151-160 - [c55]Keheliya Gallaba, Maxime Lamothe, Shane McIntosh:
Lessons from Eight Years of Operational Data from a Continuous Integration Service: An Exploratory Case Study of CircleCI. ICSE 2022: 1330-1342 - [c54]Farshad Kazemi, Maxime Lamothe, Shane McIntosh:
Exploring the Notion of Risk in Code Reviewer Recommendation. ICSME 2022: 139-150 - [e3]Shane McIntosh, Weiyi Shang, Gema Rodríguez-Pérez:
Proceedings of the 18th International Conference on Predictive Models and Data Analytics in Software Engineering, PROMISE 2022, Singapore, Singapore, 17 November 2022. ACM 2022, ISBN 978-1-4503-9860-2 [contents] - 2021
- [j21]Christian Macho, Stefanie Beyer, Shane McIntosh, Martin Pinzger:
The nature of build changes. Empir. Softw. Eng. 26(3): 32 (2021) - [j20]Bodin Chinthanet, Raula Gaikovina Kula, Shane McIntosh, Takashi Ishio, Akinori Ihara, Kenichi Matsumoto:
Lags in the release, adoption, and propagation of npm vulnerability fixes. Empir. Softw. Eng. 26(3): 47 (2021) - [j19]Farida Elzanaty, Christophe Rezk, Sander Lijbrink, Willem van Bergen, Mark Coté, Shane McIntosh:
Automatic Recovery of Missing Issue Type Labels. IEEE Softw. 38(3): 35-42 (2021) - [c53]Ian X. Gauthier, Maxime Lamothe, Gunter Mussbacher, Shane McIntosh:
Is Historical Data an Appropriate Benchmark for Reviewer Recommendation Systems? : A Case Study of the Gerrit Community. ASE 2021: 30-41 - [c52]Jeongju Sohn, Yasutaka Kamei, Shane McIntosh, Shin Yoo:
Leveraging Fault Localisation to Enhance Defect Prediction. SANER 2021: 284-294 - [e2]Shane McIntosh, Xin Xia, Sousuke Amasaki:
PROMISE '21: 17th International Conference on Predictive Models and Data Analytics in Software Engineering, Athens Greece, August 19-20, 2021. ACM 2021, ISBN 978-1-4503-8680-7 [contents] - [i9]Tao Xiao, Dong Wang, Shane McIntosh, Hideaki Hata, Raula Gaikovina Kula, Takashi Ishio, Kenichi Matsumoto:
Characterizing and Mitigating Self-Admitted Build Debt. CoRR abs/2102.09775 (2021) - [i8]Mehran Meidani, Maxime Lamothe, Shane McIntosh:
Assessing the Exposure of Software Changes: The DiPiDi Approach. CoRR abs/2104.00725 (2021) - [i7]Toshiki Hirao, Shane McIntosh, Akinori Ihara, Kenichi Matsumoto:
Code Reviews with Divergent Review Scores: An Empirical Study of the OpenStack and Qt Communities. CoRR abs/2104.01537 (2021) - 2020
- [j18]Ayse Tosun, Shane McIntosh, Leandro L. Minku, Burak Turhan:
Guest Editorial: Special Issue on Predictive Models and Data Analytics in Software Engineering. Empir. Softw. Eng. 25(2): 1533-1535 (2020) - [j17]Keheliya Gallaba, Shane McIntosh:
Use and Misuse of Continuous Integration Features: An Empirical Study of Projects That (Mis)Use Travis CI. IEEE Trans. Software Eng. 46(1): 33-50 (2020) - [c51]Younes Boubekeur, Gunter Mussbacher, Shane McIntosh:
Automatic assessment of students' software models using a simple heuristic and machine learning. MoDELS (Companion) 2020: 20:1-20:10 - [c50]Suhaib Mujahid, Rabe Abdalkareem, Emad Shihab, Shane McIntosh:
Using Others' Tests to Identify Breaking Updates. MSR 2020: 466-476
2010 – 2019
- 2019
- [j16]Chakkrit Tantithamthavorn, Shane McIntosh, Ahmed E. Hassan, Kenichi Matsumoto:
The Impact of Automated Parameter Optimization on Defect Prediction Models. IEEE Trans. Software Eng. 45(7): 683-711 (2019) - [c49]Durham Abric, Oliver E. Clark, Matthew Caminiti, Keheliya Gallaba, Shane McIntosh:
Can duplicate questions on stack overflow benefit the software development community? MSR 2019: 230-234 - [c48]Toshiki Hirao, Shane McIntosh, Akinori Ihara, Kenichi Matsumoto:
The review linkage graph for code review analytics: a recovery approach and empirical study. ESEC/SIGSOFT FSE 2019: 578-589 - [c47]Puneet Kaur Sidhu, Gunter Mussbacher, Shane McIntosh:
Reuse (or Lack Thereof) in Travis CI Specifications: An Empirical Study of CI Phases and Commands. SANER 2019: 524-533 - [i6]Shane McIntosh, Yasutaka Kamei, Meiyappan Nagappan:
Release Engineering for Mobile Applications (NII Shonan Meeting 152). NII Shonan Meet. Rep. 2019 (2019) - 2018
- [j15]Daniel Alencar da Costa, Shane McIntosh, Uirá Kulesza, Ahmed E. Hassan, Surafel Lemma Abebe:
An empirical study of the integration time of fixed issues. Empir. Softw. Eng. 23(1): 334-383 (2018) - [j14]Daniel Alencar da Costa, Shane McIntosh, Christoph Treude, Uirá Kulesza, Ahmed E. Hassan:
The impact of rapid release cycles on the integration delay of fixed issues. Empir. Softw. Eng. 23(2): 835-904 (2018) - [j13]Shane McIntosh, Yasutaka Kamei:
Are Fix-Inducing Changes a Moving Target? A Longitudinal Case Study of Just-In-Time Defect Prediction. IEEE Trans. Software Eng. 44(5): 412-428 (2018) - [c46]Le An, Foutse Khomh, Shane McIntosh, Marco Castelluccio:
Why Did This Reviewed Code Crash? An Empirical Study of Mozilla Firefox. APSEC 2018: 396-405 - [c45]Farida Elzanaty, Toshiki Hirao, Shane McIntosh, Akinori Ihara, Kenichi Matsumoto:
An empirical study of design discussions in code review. ESEM 2018: 11:1-11:10 - [c44]Shane McIntosh, Yasutaka Kamei:
Are fix-inducing changes a moving target?: a longitudinal case study of just-in-time defect prediction. ICSE 2018: 560 - [c43]Martin P. Robillard, Mathieu Nassif, Shane McIntosh:
Threats of Aggregating Software Repository Data. ICSME 2018: 508-518 - [c42]Ruiyin Wen, David Gilbert, Michael G. Roche, Shane McIntosh:
BLIMP Tracer: Integrating Build Impact Analysis with Code Review. ICSME 2018: 685-694 - [c41]Martin P. Robillard, Mathieu Nassif, Shane McIntosh:
Replication Package for "Threats of Aggregating Software Repository Data". ICSME 2018: 710 - [c40]Keheliya Gallaba, Christian Macho, Martin Pinzger, Shane McIntosh:
Noise and heterogeneity in historical build data: an empirical study of Travis CI. ASE 2018: 87-97 - [c39]Rahul Amlekar, Andrés Felipe Rincón Gamboa, Keheliya Gallaba, Shane McIntosh:
Do software engineers use autocompletion features differently than other developers? MSR 2018: 86-89 - [c38]Noam Rabbani, Michael S. Harvey, Sadnan Saquif, Keheliya Gallaba, Shane McIntosh:
Revisiting "programmers' build errors" in the visual studio context: a replication study using IDE interaction traces. MSR 2018: 98-101 - [c37]Christian Macho, Shane McIntosh, Martin Pinzger:
Automatically repairing dependency-related build breakage. SANER 2018: 106-117 - [c36]Patanamon Thongtanunam, Shane McIntosh, Ahmed E. Hassan, Hajimu Iida:
Review participation in modern code review: An empirical study of the Android, Qt, and OpenStack projects (journal-first abstract). SANER 2018: 475 - [e1]Burak Turhan, Ayse Tosun, Shane McIntosh:
Proceedings of the 14th International Conference on Predictive Models and Data Analytics in Software Engineering, PROMISE 2018, Oulu, Finland, October 10, 2018. ACM 2018 [contents] - [i5]Chakkrit Tantithamthavorn, Shane McIntosh, Ahmed E. Hassan, Kenichi Matsumoto:
The Impact of Automated Parameter Optimization on Defect Prediction Models. CoRR abs/1801.10270 (2018) - 2017
- [j12]Patanamon Thongtanunam, Shane McIntosh, Ahmed E. Hassan, Hajimu Iida:
Review participation in modern code review - An empirical study of the android, Qt, and OpenStack projects. Empir. Softw. Eng. 22(2): 768-817 (2017) - [j11]Cor-Paul Bezemer, Shane McIntosh, Bram Adams, Daniel M. Germán, Ahmed E. Hassan:
An empirical study of unspecified dependencies in make-based build systems. Empir. Softw. Eng. 22(6): 3117-3148 (2017) - [j10]Chakkrit Tantithamthavorn, Shane McIntosh, Ahmed E. Hassan, Kenichi Matsumoto:
An Empirical Comparison of Model Validation Techniques for Defect Prediction Models. IEEE Trans. Software Eng. 43(1): 1-18 (2017) - [j9]Feng Zhang, Ahmed E. Hassan, Shane McIntosh, Ying Zou:
The Use of Summation to Aggregate Software Metrics Hinders the Performance of Defect Prediction Models. IEEE Trans. Software Eng. 43(5): 476-491 (2017) - [j8]Daniel Alencar da Costa, Shane McIntosh, Weiyi Shang, Uirá Kulesza, Roberta Coelho, Ahmed E. Hassan:
A Framework for Evaluating the Results of the SZZ Approach for Identifying Bug-Introducing Changes. IEEE Trans. Software Eng. 43(7): 641-657 (2017) - [c35]Qi Cao, Ruiyin Wen, Shane McIntosh:
Forecasting the Duration of Incremental Build Jobs. ICSME 2017: 524-528 - [c34]Baljinder Ghotra, Shane McIntosh, Ahmed E. Hassan:
A large-scale study of the impact of feature selection techniques on defect classification models. MSR 2017: 146-157 - [c33]Christian Macho, Shane McIntosh, Martin Pinzger:
Extracting build changes with BuildDiff. MSR 2017: 368-378 - [c32]Marco Manglaviti, Eduardo Coronado-Montoya, Keheliya Gallaba, Shane McIntosh:
An empirical study of the personnel overhead of continuous integration. MSR 2017: 471-474 - [c31]Yash Gupta, Yusaira Khan, Keheliya Gallaba, Shane McIntosh:
The impact of the adoption of continuous integration on developer attraction and retention. MSR 2017: 491-494 - [i4]Christian Macho, Shane McIntosh, Martin Pinzger:
Extracting Build Changes with BUILDDIFF. CoRR abs/1703.08527 (2017) - 2016
- [j7]Shane McIntosh, Bram Adams, Meiyappan Nagappan, Ahmed E. Hassan:
Identifying and understanding header file hotspots in C/C++ build processes. Autom. Softw. Eng. 23(4): 619-647 (2016) - [j6]Yasutaka Kamei, Takafumi Fukushima, Shane McIntosh, Kazuhiro Yamashita, Naoyasu Ubayashi, Ahmed E. Hassan:
Studying just-in-time defect prediction using cross-project models. Empir. Softw. Eng. 21(5): 2072-2106 (2016) - [j5]Shane McIntosh, Yasutaka Kamei, Bram Adams, Ahmed E. Hassan:
An empirical study of the impact of modern code review practices on software quality. Empir. Softw. Eng. 21(5): 2146-2189 (2016) - [j4]Kazuhiro Yamashita, Yasutaka Kamei, Shane McIntosh, Ahmed E. Hassan, Naoyasu Ubayashi:
Magnet or Sticky? Measuring Project Characteristics from the Perspective of Developer Attraction and Retention. J. Inf. Process. 24(2): 339-348 (2016) - [j3]Chakkrit Tantithamthavorn, Shane McIntosh, Ahmed E. Hassan, Kenichi Matsumoto:
Comments on "Researcher Bias: The Use of Machine Learning in Software Defect Prediction". IEEE Trans. Software Eng. 42(11): 1092-1094 (2016) - [c30]Keisuke Miura, Shane McIntosh, Yasutaka Kamei, Ahmed E. Hassan, Naoyasu Ubayashi:
The Impact of Task Granularity on Co-evolution Analyses. ESEM 2016: 47:1-47:10 - [c29]Junji Shimagaki, Yasutaka Kamei, Shane McIntosh, Ahmed E. Hassan, Naoyasu Ubayashi:
A study of the quality-impacting practices of modern code review at Sony mobile. ICSE (Companion Volume) 2016: 212-221 - [c28]Chakkrit Tantithamthavorn, Shane McIntosh, Ahmed E. Hassan, Kenichi Matsumoto:
Automated parameter optimization of classification techniques for defect prediction models. ICSE 2016: 321-332 - [c27]Patanamon Thongtanunam, Shane McIntosh, Ahmed E. Hassan, Hajimu Iida:
Revisiting code ownership and its relationship with software quality in the scope of modern code review. ICSE 2016: 1039-1050 - [c26]Junji Shimagaki, Yasutaka Kamei, Shane McIntosh, David Pursehouse, Naoyasu Ubayashi:
Why are Commits Being Reverted?: A Comparative Study of Industrial and Open Source Projects. ICSME 2016: 301-311 - [c25]Daniel Alencar da Costa, Shane McIntosh, Uirá Kulesza, Ahmed E. Hassan:
The impact of switching to a rapid release cycle on the integration delay of addressed issues: an empirical study of the mozilla firefox project. MSR 2016: 374-385 - [c24]Casimir Désarmeaux, Andrea Pecatikov, Shane McIntosh:
The dispersion of build maintenance activity across maven lifecycle phases. MSR 2016: 492-495 - [c23]Jacob G. Barnett, Charles K. Gathuru, Luke S. Soldano, Shane McIntosh:
The relationship between commit message detail and defect proneness in Java projects on GitHub. MSR 2016: 496-499 - [c22]Bram Adams, Shane McIntosh:
Modern Release Engineering in a Nutshell - Why Researchers Should Care. FOSE@SANER 2016: 78-90 - [c21]Moritz Beller, Radjino Bholanath, Shane McIntosh, Andy Zaidman:
Analyzing the State of Static Analysis: A Large-Scale Evaluation in Open Source Software. SANER 2016: 470-481 - [c20]Christian Macho, Shane McIntosh, Martin Pinzger:
Predicting Build Co-changes with Source Code Change and Commit Categories. SANER 2016: 541-551 - [i3]Chakkrit Tantithamthavorn, Shane McIntosh, Ahmed E. Hassan, Ken-ichi Matsumoto:
Comments on "Researcher bias: The use of machine learning in software defect prediction". PeerJ Prepr. 4: e1260 (2016) - 2015
- [b1]Shane McIntosh:
Studying the Software Development Overhead of Build Systems. Queen's University at Kingston, Ontario, Canada, 2015 - [j2]Shane McIntosh, Meiyappan Nagappan, Bram Adams, Audris Mockus, Ahmed E. Hassan:
A Large-Scale Empirical Study of the Relationship between Build Technology and Build Maintenance. Empir. Softw. Eng. 20(6): 1587-1633 (2015) - [c19]Baljinder Ghotra, Shane McIntosh, Ahmed E. Hassan:
Revisiting the Impact of Classification Techniques on the Performance of Defect Prediction Models. ICSE (1) 2015: 789-800 - [c18]Chakkrit Tantithamthavorn, Shane McIntosh, Ahmed E. Hassan, Akinori Ihara, Ken-ichi Matsumoto:
The Impact of Mislabelling on the Performance and Interpretation of Defect Prediction Models. ICSE (1) 2015: 812-823 - [c17]Kazuhiro Yamashita, Shane McIntosh, Yasutaka Kamei, Ahmed E. Hassan, Naoyasu Ubayashi:
Revisiting the applicability of the pareto principle to core development teams in open source software projects. IWPSE 2015: 46-55 - [c16]Patanamon Thongtanunam, Shane McIntosh, Ahmed E. Hassan, Hajimu Iida:
Investigating Code Review Practices in Defective Files: An Empirical Study of the Qt System. MSR 2015: 168-179 - [c15]Meiyappan Nagappan, Romain Robbes, Yasutaka Kamei, Éric Tanter, Shane McIntosh, Audris Mockus, Ahmed E. Hassan:
An empirical study of goto in C code from GitHub repositories. ESEC/SIGSOFT FSE 2015: 404-414 - [c14]Rodrigo Morales, Shane McIntosh, Foutse Khomh:
Do code review practices impact design quality? A case study of the Qt, VTK, and ITK projects. SANER 2015: 171-180 - [c13]Xin Xia, David Lo, Shane McIntosh, Emad Shihab, Ahmed E. Hassan:
Cross-project build co-change prediction. SANER 2015: 311-320 - [i2]Chakkrit Tantithamthavorn, Shane McIntosh, Ahmed E. Hassan, Ken-ichi Matsumoto:
Comments on "Researcher bias: The use of machine learning in software defect prediction". PeerJ Prepr. 3: e1260 (2015) - [i1]Meiyappan Nagappan, Romain Robbes, Yasutaka Kamei, Éric Tanter, Shane McIntosh, Audris Mockus, Ahmed E. Hassan:
An empirical study of goto in C code. PeerJ Prepr. 3: e826 (2015) - 2014
- [c12]Shane McIntosh, Katie Legere, Ahmed E. Hassan:
Orchestrating change: An artistic representation of software evolution. CSMR-WCRE 2014: 348-352 - [c11]