Masud Rahman, Ph.D.   
 
 
Assistant Professor, Faculty of Computer Science, Dalhousie University, Canada

"And say: My Lord increase me in knowledge." -(The Qur'an, Ta-Ha 20:114)

 
Masud
 

 

Research Publications

journal article conference paper dissertation poster technical report

Journals

2024 (4)
  • Towards Enhancing the Reproducibility of Deep Learning Bugs: An Empirical Study
    [J9] Mehil Shah, M. Masudur Rahman, and Foutse Khomh. Towards Enhancing the Reproducibility of Deep Learning Bugs: An Empirical Study. Journal of Empirical Software Engineering (EMSE), pp. 57
    Impact Factor = 3.48, Download PDF: , Cite this: , Replication package:  
  • On the Prevalence, Evolution, and Impact of Code Smells in Simulation Modelling Software
    [C42] Riasat Mahbub, M. Masudur Rahman, and M. Ahsan Habib. On the Prevalence, Evolution, and Impact of Code Smells in Simulation Modelling Software. In Proceeding of The 24th IEEE International Working Conference on Source Code Analysis and Manipulation (SCAM) (SCAM 2024), pp. 12, Flagstaff, AZ, USA, October 2024 (To appear).
    Acceptance rate: TBA, Reviewed: Double-blind, Download PDF: , Cite this: , Slides: , Replication package:  
  • Predicting Line-Level Defects by Capturing Code Contexts with Hierarchical Transformers
    [C41] Parvez Mahbub and M. Masudur Rahman. Predicting Line-Level Defects by Capturing Code Contexts with Hierarchical Transformers. In Proceeding of The 31st IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER 2024), pp. 12, Rovaniemi, Finland, March 2024 (To appear).
    Acceptance rate: 25.6%, Reviewed: Double-blind, Download PDF: , Cite this: , Slides: , Replication package:  
  • Can We Identify Stack Overflow Questions Requiring Code Snippets? Investigating the Cause & Effect of Missing Code Snippets
    [C40] Saikat Mondal, M. Masudur Rahman and Chanchal K. Roy. Can We Identify Stack Overflow Questions Requiring Code Snippets? Investigating the Cause & Effect of Missing Code Snippets. In Proceeding of The 31st IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER 2024), pp. 12, Rovaniemi, Finland, March 2024 (To appear).
    Acceptance rate: 25.6%, Reviewed: Double-blind, Download PDF: , Cite this: , Slides: , Replication package:  

2023 (7)
  • Explaining Software Bugs Leveraging Code Structures in Neural Machine Translation
    [C39] Parvez Mahbub, Ohiduzzaman Shuvo, and M. Masudur Rahman. Explaining Software Bugs Leveraging Code Structures in Neural Machine Translation. In Proceeding of The 45th IEEE/ACM International Conference on Software Engineering (ICSE 2023), pp. 12, Melbourne, Australia, May 2023 (To appear).
    Acceptance rate: 26.00%, Reviewed: Double-blind, Download PDF: , Cite this: , Slides: , Replication package:    
  • A Systematic Review of Automated Query Reformulations in Source Code Search
    [J7] M. Masudur Rahman and Chanchal K. Roy. A Systematic Review of Automated Query Reformulations in Source Code Search. ACM Transactions on Software Engineering and Methodology (TOSEM), pp. 81
    Impact Factor = 3.685, Download PDF: , Cite this: , Replication package:  
  • Recommending Code Reviews Leveraging Code Changes with Structured Information Retrieval
    [C38] Ohiduzzaman Shuvo, Parvez Mahbub, and M. Masudur Rahman. Recommending Code Reviews Leveraging Code Changes with Structured Information Retrieval. In Proceeding of The 39th IEEE International Conference on Software Maintenance and Evolution (ICSME 2023), pp. 12, Bogota, Columbia, October 2023 (To appear).
    Acceptance rate: 22.70%, Reviewed: Double-blind, Download PDF: , Cite this: , Slides: , Replication package:  
  • Towards Understanding the Impacts of Textual Dissimilarity on Duplicate Bug Report Detection
    [C37] Sigma Jahan and M. Masudur Rahman. Towards Understanding the Impacts of Textual Dissimilarity on Duplicate Bug Report Detection. In Proceeding of The 30th IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER 2023), pp. 12, Macao, China, March 2023 (To appear).
    Acceptance rate: 27.00%, Reviewed: Double-blind, Download PDF: , Cite this: , Slides: , Replication package:  
  • Do Subjectivity and Objectivity Always Agree? A Case Study with Stack Overflow Questions
    [C36] Saikat Mondal, M. Masudur Rahman, and Chanchal K. Roy. Do Subjectivity and Objectivity Always Agree? A Case Study with Stack Overflow Questions. In Proceeding of The 20th International Conference on Mining Software Repositories (MSR 2023), pp. 12, Melbourne, Australia, May 2023 (To appear).
    Acceptance rate: 37.00%, Reviewed: Double-blind, Download PDF: , Cite this: , Slides: , Replication package:  
  • Bugsplainer: Leveraging Code Structures to Explain Software Bugs with Neural Machine Translation
    [C35] Parvez Mahbub, M. Masudur Rahman, Ohiduzzaman Shuvo, Avinash Gopal. Bugsplainer: Leveraging Code Structures to Explain Software Bugs with Neural Machine Translation. In Proceeding of The 39th IEEE International Conference on Software Maintenance and Evolution (ICSME 2023), pp. 06, Bogota, Columbia, October 2023 (To appear).
    Acceptance rate: 61.00%, Reviewed: Single-blind, Download PDF: , Cite this: , Slides: , Replication package:  
  • Defectors: A Large, Diverse Python Dataset for Defect Prediction
    [C34] Parvez Mahbub, Ohiduzzaman Shuvo, and M. Masudur Rahman. Defectors: A Large, Diverse Python Dataset for Defect Prediction. In Proceeding of The 20th International Conference on Mining Software Repositories (MSR 2023), pp. 5, Melbourne, Australia, May 2023 (To appear).
    Acceptance rate: 54.00%, Reviewed: Single-blind, Download PDF: , Cite this: , Slides: , Replication package:  

2022 (2)

2021 (5)
  • The Forgotten Role of Search Queries in IR-based Bug Localization: An Empirical Study
    [J4] M. Masudur Rahman, F. Khomh, S. Yeasmin, and C. K. Roy. The Forgotten Role of Search Queries in IR-based Bug Localization: An Empirical Study. Journal of Empirical Software Engineering (EMSE), pp. 57.
    Impact Factor = 3.48, Download PDF: , Cite this: , Replication package:  

  • The Reproducibility of Programming-Related Issues in Stack Overflow Questions
    [J5] Saikat Mondal, M. Masudur Rahman, Chanchal K. Roy, and Kevin A. Schneider. The Reproducibility of Programming-Related Issues in Stack Overflow Questions. Journal of Empirical Software Engineering (EMSE), pp. 58
    Impact Factor = 3.48, Download PDF: , Cite this: , Replication package:  
  • Summarizing Relevant Parts from Technical Videos
    [C33] Mahmood Vahedi, M. Masudur Rahman, Foutse Khomh, Gias Uddin and Giuliano Antoniol. Summarizing Relevant Parts from Technical Videos. In Proceeding of The 28th IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER 2021), pp. 12, Honolulu, HI, USA, March 2021 (In Press).
    Acceptance rate: 25.00%, Reviewed: Double-blind, Download PDF: , Cite this: , Slides: , Replication package:  
  • Improved Retrieval of Programming Solutions With Code Examples Using a Multi-featured Score.
    [J3] Rodrigo F. Silva, M. Masudur Rahman, Carlos Eduardo Dantas, Chanchal Roy, Foutse Khomh, and Marcelo A. Maia. Improved Retrieval of Programming Solutions With Code Examples Using a Multi-featured Score. Journal of Systems and Software (JSS), pp. 31, August 2021.
    Impact Factor = 2.83, Download PDF: , Cite this: , Replication package:  
  • Early Detection and Guidelines to Improve Unanswered Questions on Stack Overflow
    [C32] Saikat Mondal, C M Khaled Saifullah, Avijit Bhattacharjee, M. Masudur Rahman and Chanchal K. Roy. Early Detection and Guidelines to Improve Unanswered Questions on Stack Overflow. In Proceeding of The 13th Innovation in Software Engineering Conference (ISEC 2021), pp. 11, Bhubaneswar, India, February 2021 (to appear).
    Acceptance rate: 33.33%, Reviewed: Double-blind, Download PDF: , Cite this: , Slides: , Replication package:  
@ARTICLE{emse2024mehil
	author={Shah, M. and Rahman, M. M. and Khomh, F.},
	journal={EMSE},
	title={Towards Enhancing the Reproducibility of Deep Learning Bugs: An Empirical Study},
	year={2024},
	pages={57}
}
@INPROCEEDINGS{scam2024riasat,
	author={Mahbub, R. and Rahman, M. M. and Habib, M. A.},
	booktitle={Proc. SCAM},
	title={On the Prevalence, Evolution, and Impact of Code Smells in Simulation Modelling Software},
	year={2024},
	pages={12}
}
@INPROCEEDINGS{saner2024parvez,
	author={Mahbub, P. and Rahman, M. M.},
	booktitle={Proc. SANER},
	title={Predicting Line-Level Defects by Capturing Code Contexts with Hierarchical Transformers},
	year={2024},
	pages={12}
}
@INPROCEEDINGS{saner2024saikat,
	author={Mondal, S. and Rahman, M. M. and Roy, C.},
	booktitle={Proc. SANER},
	title={Can We Identify Stack Overflow Questions Requiring Code Snippets? Investigating the Cause & Effect of Missing Code Snippets},
	year={2024},
	pages={12}
}
@ARTICLE{tosem2023masud,
	author={Rahman, M. M. and Roy, C. K.},
	journal={TOSEM},
	title={A Systematic Review of Automated Query Reformulations in Source Code Search},
	year={2023},
	pages={81}
}
@INPROCEEDINGS{msrdata2023parvez,
	author={Mahbub, P. and Shuvo, O. and Rahman, M. M.},
	booktitle={Proc. MSR},
	title={Defectors: A Large, Diverse Python Dataset for Defect Prediction},
	year={2023},
	pages={05}
}
@INPROCEEDINGS{msr2023saikat,
	author={Mondal, S. and Rahman, M. M. and Roy, C.},
	booktitle={Proc. MSR},
	title={Do Subjectivity and Objectivity Always Agree? A Case Study with Stack Overflow Questions},
	year={2023},
	pages={12}
}
@INPROCEEDINGS{icsme2023shuvo,
	author={Shuvo, O., and Mahbub, P., and Rahman, M. M.},
	booktitle={Proc. ICSME},
	title={Recommending Code Reviews Leveraging Code Changes with Structured Information Retrieval},
	year={2023},
	pages={12}
}
@INPROCEEDINGS{icsme2023parvez,
	author={Mahbub, P., and Rahman, M. M., and Shuvo, O. and Gopal, A.},
	booktitle={Proc. ICSME},
	title={Bugsplainer: Leveraging Code Structures to Explain Software Bugs with Neural Machine Translation},
	year={2023},
	pages={06}
}
@INPROCEEDINGS{icse2023parvez,
	author={Mahbub, P., and Shuvo, O., and Rahman, M. M.},
	booktitle={Proc. ICSE},
	title={ Explaining Software Bugs Leveraging Code Structures in Neural Machine Translation},
	year={2023},
	pages={12}
}
@INPROCEEDINGS{saner2023sigma,
	author={Jahan, S. and Rahman, M. M.},
	booktitle={Proc. SANER},
	title={Towards Understanding the Impacts of Textual Dissimilarity on Duplicate Bug Report Detection},
	year={2023},
	pages={12}
}
@ARTICLE{emse2022masud,
	author={Rahman, M. M. and Khomh, F. and Castelluccio, M.},
	journal={EMSE},
	title={Works for Me! Cannot Reproduce -- A Large Scale Empirical Study of Non-reproducible Bugs},
	year={2022},
	pages={44}
}
@ARTICLE{emse2021bmondal,
	author={Mondal, S. and Rahman, M. M. and Roy, C. K. and Schneider, K. A.},
	journal={EMSE},
	title={The Reproducibility of Programming-Related Issues in Stack Overflow Questions},
	year={2021},
	pages={58}
}
@ARTICLE{emse2021masud,
	author={Rahman, M. M. and Khomh, F. and Yeasmin, S. and Roy, C. K.},
	journal={EMSE},
	title={The Forgotten Role of Search Queries in IR-based Bug Localization: An Empirical Study},
	year={2021},
	pages={57}
}
@ARTICLE{jss2021rodrigo,
	author={Silva, R. F. and  Rahman, M. M. and Dantas, C. E. and Roy, C. and  Khomh, F. and Maia, M. A.},
	journal={JSS},
	title={Improved Retrieval of Programming Solutions With Code Examples Using a Multi-featured Score},
	year={2021},
	pages={31}
}
@INPROCEEDINGS{saner2021vahedi,
	author={Vahedi, M. and  Rahman, M.M. and Khomh, F. and Uddin, G. and Antoniol, G.},
	booktitle={Proc. SANER},
	title={Summarizing Relevant Parts from Technical Videos},
	year={2021},
	pages={12}
}
@INPROCEEDINGS{isec2021mondal,
	author={Mondal, S. and Saifullah, C. M. K. and Bhattacharjee, A. and Rahman, M. M. and Roy, C. K.},
	booktitle={Proc. ISEC},
	title={Early Detection and Guidelines to Improve Unanswered Questions on Stack Overflow},
	year={2021},
	pages={12}
}

2020 (4)

  • CROKAGE: Effective Solution Recommendations for Programming Tasks by Leveraging Crowd Knowledge
    [J2] Rodrigo F. G. Da Silva, Chanchal K. Roy, M. Masudur Rahman, Kevin Schneider, Klerisson Paixao, Marcelo Maia and C. E. Dantas. CROKAGE: Effective Solution Recommendations for Programming Tasks by Leveraging Crowd Knowledge. Journal of Empirical Software Engineering (EMSE), 47 pp., June 2020
    Impact Factor = 4.46, Download PDF: , Cite this: , Replication package:  

  • The Scent of Deep Learning Code: An Empirical Study
    [C30] Hadhemi Jebnoun, Houssem Ben Braiek, M. Masudur Rahman and Foutse Khomh. The Scent of Deep Learning Code: An Empirical Study. In Proceeding of The 17th International Conference on Mining Software Repositories (MSR 2020), pp. 11, Seoul, South Korea, May, 2020 (In press)
    Acceptance rate: 29.70%, Reviewed: Double-blind, Download PDF: , Cite this: , Slides: , Replication package:  

  • On the Prevalence, Impact, and Evolution of SQLcode smells in Data-Intensive Systems
    [C29] Biruk Asmare Muse, M. Masudur Rahman, Csaba Nagy, Anthony Cleve, Foutse Khomh and Giuliano Antoniol. On the Prevalence, Impact, and Evolution of SQLcode smells in Data-Intensive Systems. In Proceeding of The 17th International Conference on Mining Software Repositories (MSR 2020), pp. 12, Seoul, South Korea, May, 2020 (In press)
    Acceptance rate: 29.70%, Reviewed: Double-blind, Download PDF: , Cite this: , Slides: , Replication package:  

2019 (3)
  • Supporting Code Search with Context-Aware, Analytics-Driven, Effective Query Reformulation
    [C28] M. Masudur Rahman. Supporting Code Search with Context-Aware, Analytics-Driven, Effective Query Reformulation. In Proceeding of The 41st ACM/IEEE International Conference on Software Engineering (Companion volume, DS track) (ICSE 2019), pp. 226--229, Montreal, Canada, May, 2019
    Acceptance rate: 29%, Reviewed: Single-blind, Download PDF: , Cite this: , Slides: , Replication package:  

  • Can Issues Reported at Stack Overflow Questions be Reproduced? An Exploratory Study
    [C27] Saikat Mondal, M. Masudur Rahman and C. K. Roy. Can Issues Reported at Stack Overflow Questions be Reproduced? An Exploratory Study. In Proceeding of The 16th International Conference on Mining Software Repositories (MSR 2019), pp. 479--489, Montreal, Canada, May, 2019
    Acceptance rate: 25.40%, Reviewed: Double-blind, Download PDF: , Cite this: , Slides: , Replication package:  

  • Recommending Comprehensive Solutions for Programming Tasks by Mining Crowd Knowledge
    [C26] Rodrigo F. G. Da Silva, Chanchal K. Roy, M. Masudur Rahman, Kevin Schneider, Klerisson Paixao and Marcelo Maia. Recommending Comprehensive Solutions for Programming Tasks by Mining Crowd Knowledge. In Proceeding of The 27th IEEE/ACM International Conference on Program Comprehension (ICPC 2019), pp. 358--368, Montreal, Canada, May, 2019 [Featured in Stack Overflow Blog*]
    Acceptance rate: 30.10%, Reviewed: Double-blind, Download PDF: , Cite this: , Slides: , Replication package:  

@ARTICLE{emse2020rodrigo,
	author={Da Silva, R. F. G. and Roy, C. K. and Rahman, M. M. and Schneider, K. and Paixao, K. and Maia, M. and Dantas, C. E.},
	journal={EMSE},
	title={CROKAGE: Effective Solution Recommendations for Programming Tasks by Leveraging Crowd Knowledge},
	year={2020},
	pages={47}
}
@INPROCEEDINGS{icsme2020masud,
	author={Rahman, M. M. and Khomh, F. and Castelluccio, M.},
	booktitle={Proc. ICSME},
	title={Why are Some Bugs Non-Reproducible? An Empirical Investigation using Data Fusion},
	year={2020},
	pages={12}
}
@INPROCEEDINGS{msr2020hadhemi,
	author={Jebnoun, H. and Braiek, H. B. and Rahman, M. M. and Khomh, F.},
	booktitle={Proc. MSR},
	title={The Scent of Deep Learning Code: An Empirical Study},
	year={2020},
	pages={11}
}
@INPROCEEDINGS{msr2020biruk,
	author={Muse, B. A. and Rahman, M. M. and Nagy, C. and  Cleve, A. and Khomh, F. and Antoniol, G.},
	booktitle={Proc. MSR},
	title={On the Prevalence, Impact, and Evolution of SQLcode smells in Data-Intensive Systems},
	year={2020},
	pages={12}
}
@INPROCEEDINGS{icse2019masud,
	author={Rahman, M. M.},
	booktitle={Proc. ICSE-C},
	title={Supporting Code Search with Context-Aware, Analytics-Driven, Effective Query Reformulation},
	year={2019},
	pages={226--229}
}
@INPROCEEDINGS{msr2019mondal,
	author={Mondal, S. and Rahman, M. M. and Roy, C. K.},
	booktitle={Proc. MSR},
	title={Can Issues Reported at Stack Overflow Questions be Reproduced? An Exploratory Study},
	year={2019},
	pages={479--489}
}
@INPROCEEDINGS{icpc2019rodrigo,
	author={Da Silva, R. F. G. and Roy, C. K. and Rahman, M. M.  and Schneider, K. and Paix�o, K. and Maia, M.},
	booktitle={Proc. ICPC},
	title={Recommending Comprehensive Solutions for Programming Tasks by Mining Crowd Knowledge},
	year={2019},
	pages={358--368}
}
2018 (5)
  • Automatic Query Reformulation for Code Search using Crowdsourced Knowledge
    [J1] M. Masudur Rahman, C. K. Roy and David Lo. Automatic Query Reformulation for Code Search using Crowdsourced Knowledge. Journal of Empirical Software Engineering (EMSE), pp. 24:1869-1924
    Impact Factor = 4.46, Download PDF: , Cite this: , Replication package:  

  • Improving IR-Based Bug Localization with Context-Aware Query Reformulation
    [C25] M. Masudur Rahman and C. K. Roy. Improving IR-Based Bug Localization with Context-Aware Query Reformulation. In Proceeding of The 26th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE 2018), pp. 621--632, Florida, USA, November, 2018 (to appear) [Artifact Badges: Functional + Available + Reusable]
    Acceptance rate: 19%, Reviewed: Double-blind, Download PDF: , Cite this: , Slides: , Replication package:  


  • Poster: Improving Bug Localization with Report Quality Dynamics and Query Reformulation
    [C23] M. Masudur Rahman and C. K. Roy. Poster: Improving Bug Localization with Report Quality Dynamics and Query Reformulation. In Proceeding of The 40th International Conference on Software Engineering (Companion volume, Poster Track) (ICSE 2018), pp. 348--349, Gothenburg, Sweden, May, 2018
    Acceptance rate: TBA, Reviewed: Double-blind, Download PDF: , Cite this: , Poster: , Replication package:  

  • NLP2API: Query Reformulation for Code Search using Crowdsourced Knowledge and Extra-Large Data Analytics
    [C22] M. Masudur Rahman and C. K. Roy. NLP2API: Query Reformulation for Code Search using Crowdsourced Knowledge and Extra-Large Data Analytics. In Proceeding of The 34th International Conference on Software Maintenance and Evolution (Artifact Track) (ICSME 2018), pp. 714, Madrid, Spain, September, 2018 (to appear) [Artifact: Accepted]
    Reviewed: Single-blind, Download PDF: , Cite this: , Slides: , Replication package:  
@INPROCEEDINGS{icse2018masud,
	author={Rahman, M. M. and Roy, C. K.},
	booktitle={Proc. ICSE-C},
	title={Improving Bug Localization with Report Quality Dynamics and Query Reformulation},
	year={2018},
	pages={348--349}
}
@ARTICLE{emse2018masud,
	author={Rahman, M. M. and Roy, C. K. and Lo, D.},
	journal={EMSE},
	title={Automatic Query Reformulation for Code Search using Crowdsourced  Knowledge},
	year={2018},
	pages={1--56}
}
@INPROCEEDINGS{icsme2018masud,
	author={Rahman, M. M. and Roy, C. K.},
	booktitle={Proc. ICSME},
	title={Effective Reformulation of Query for Code Search using Crowdsourced Knowledge and Extra-Large Data Analytics},
	year={2018},
	pages={516--527}
}
@INPROCEEDINGS{icsme2018masudb,
	author={Rahman, M. M. and Roy, C. K.},
	booktitle={Proc. ICSME},
	title={NLP2API: Query Reformulation for Code Search using Crowdsourced Knowledge and Extra-Large Data Analytics },
	year={2018},
	pages={714}
}
@INPROCEEDINGS{fse2018masud,
	author={Rahman, M. M. and Roy, C. K.},
	booktitle={Proc. ESEC/FSE},
	title={Improving IR-Based Bug Localization with Context-Aware Query Reformulation},
	year={2018},
	pages={621--632}
}

2017 (5)
  • Improved Query Reformulation for Concept Location using CodeRank and Document Structures
    [C21] M. Masudur Rahman and C. K. Roy. Improved Query Reformulation for Concept Location using CodeRank and Document Structures. In Proceeding of The 32nd International Conference on Automated Software Engineering (ASE 2017), pp. 428-439, Urbana-Champaign, Illinois, USA, October, 2017
    Acceptance rate: 21%, Reviewed: Double-blind, Download PDF: , Cite this: , Slides: , Replication package:  

  • Predicting Usefulness of Code Review Comments using Textual Features and Developer Experience
    [C20] M. Masudur Rahman and C. K. Roy and R.G. Kula. Predicting Usefulness of Code Review Comments using Textual Features and Developer Experience. In Proceeding of The 14th International Conference on Mining Software Repositories (MSR 2017), pp. 215--226, Buenos Aires, Argentina, May, 2017
    Acceptance rate: 30.60%, Reviewed: Double-blind, Download PDF: , Cite this: , Slides: , Replication package:  

  • RACK: Code Search in the IDE using Crowdsourced Knowledge
    [C19] M. Masudur Rahman and C. K. Roy and David Lo. RACK: Code Search in the IDE using Crowdsourced Knowledge. In Proceeding of The 39th International Conference on Software Engineering (Companion volume) (ICSE 2017), pp. 51--54, Buenos Aires, Argentina, May, 2017
    Acceptance rate: 31.58%, Reviewed: Double-blind, Download PDF: , Cite this: , Slides: , Replication package:    

  • Impact of Continuous Integration on Code Reviews
    [C18] M. Masudur Rahman and C. K. Roy. Impact of Continuous Integration on Code Reviews. In Proceeding of The The 14th International Conference on Mining Software Repositories (MSR 2017), pp. 499--502, Buenos Aires, Argentina, May, 2017
    Reviewed: Double-blind, Download PDF: , Cite this: , Slides: , Replication package:  

  • STRICT: Information Retrieval Based Search Term Identification for Concept Location
    [C17] M. Masudur Rahman and C. K. Roy. STRICT: Information Retrieval Based Search Term Identification for Concept Location. In Proceeding of The 24th IEEE International Conference on Software Analysis, Evolution, and Reengineering (SANER 2017), pp. 79--90, Klagenfurt, Austria, February 2017
    Acceptance rate: 24%, Reviewed: Double-blind, Download PDF: , Cite this: , Slides: , Replication package:  
@INPROCEEDINGS{ase2017masud,
	author={Rahman, M. M. and Roy, C. K.},
	booktitle={Proc. ASE},
	title={Improved Query Reformulation for Concept Location using CodeRank and Document Structures},
	year={2017},
	pages={428-439}
}
@INPROCEEDINGS{saner2017masud,
	author={Rahman, M. M. and Roy, C. K.},
	booktitle={Proc. SANER},
	title={{STRICT}: {Information Retrieval Based Search Term Identification for Concept Location}},
	year={2017},
	pages={79--90}
}
@INPROCEEDINGS{msr2017amasud,
	author={Rahman, M. M. and Roy, C. K. and Kula, R. G.},
	booktitle={Proc. MSR},
	title={Predicting Usefulness of Code Review Comments using Textual Features and Developer Experience},
	year={2017},
	pages={215--226}
}
@INPROCEEDINGS{msr2017bmasud,
	author={Rahman, M. M. and Roy, C. K.},
	booktitle={Proc. MSR},
	title={Impact of Continuous Integration on Code Reviews},
	year={2017},
	pages={499--502}
}
@INPROCEEDINGS{icse2017masud,
	author={Rahman, M. M. and Roy, C. K. and Lo, D.},
	booktitle={Proc. ICSE-C},
	title={RACK: Code Search in the IDE using Crowdsourced Knowledge},
	year={2017},
	pages={51--54}
}

2016 (5)
  • QUICKAR: Automatic Query Reformulation for Concept Location Using Crowdsourced Knowledge
    [C16] M. Masudur Rahman and C. K. Roy. QUICKAR: Automatic Query Reformulation for Concept Location Using Crowdsourced Knowledge. In Proceeding of The 31st IEEE/ACM International Conference on Automated Software Engineering (ASE 2016), pp. 220--225, Singapore, September 2016
    Reviewed: Double-blind, Download PDF: , Cite this: , Slides: , Replication package:  

  • CORRECT: Code Reviewer Recommendation at GitHub for Vendasta Technologies
    [C15] M. Masudur Rahman, C. K. Roy, Jesse Redl, and Jason Collins. CORRECT: Code Reviewer Recommendation at GitHub for Vendasta Technologies. In Proceeding of The 31st IEEE/ACM International Conference on Automated Software Engineering (ASE 2016), pp. 792--797, Singapore, September 2016
    Reviewed: Single-blind, Download PDF: , Cite this: , Slides: , Replication package:    

  • CORRECT: Code Reviewer Recommendation in GitHub Based on Cross-Project and Technology Experience
    [C14] M. Masudur Rahman, C. K. Roy, and Jason Collins. CORRECT: Code Reviewer Recommendation in GitHub Based on Cross-Project and Technology Experience. In Proceeding of The 38th International Conference on Software Engineering (Companion volume) (ICSE 2016), pp. 222--231, Austin Texas, USA, May 2016
    Acceptance rate: 26%, Reviewed: Single-blind, Download PDF: , Cite this: , Slides: , Replication package:  

  • RACK: Automatic API Recommendation using Crowdsourced Knowledge
    [C13] M. Masudur Rahman, C. K. Roy and David Lo. RACK: Automatic API Recommendation using Crowdsourced Knowledge. In Proceeding of The 23rd IEEE International Conference on Software Analysis, Evolution, and Reengineering (SANER 2016), pp. 349--359, Osaka, Japan, March 2016
    Acceptance rate: 37%, Reviewed: Single-blind, Download PDF: , Cite this: , Slides: , Replication package:  

  • Embedded Emotion-based Classification of Stack Overflow Questions Towards the Question Quality Prediction
    [C12] Amit K. Mondal, M. Masudur Rahman and C. K. Roy. Embedded Emotion-based Classification of Stack Overflow Questions Towards the Question Quality Prediction. In Proceeding of The 28th International Conference on Software Engineering & Knowledge Engineering (SEKE 2016), pp. 521-526, San Francisco Bay, California, USA, July 2016
    Acceptance rate: 29.7%, Reviewed: Single-blind, Download PDF: , Cite this: , Slides: , Replication package:  
@INPROCEEDINGS{saner2016masud,
	author={Rahman, M. M. and Roy, C. K. and Lo, D.},
	booktitle={Proc. SANER},
	title={{RACK}: {A}utomatic {API} {R}ecommendation using {C}rowdsourced {K}nowledge},
	year={2016},
	pages={349--359}
}
@inproceedings{icse2016masud,
	 author={Rahman, M. M. and Roy, C. K. and Collins, J.},
	 title ={{CORRECT: Code Reviewer Recommendation Based on Cross-Project and Technology Experience}},
	 booktitle = {Proc. ICSE-C},
	 year = {2016},
	 pages = {222--231}
}
@inproceedings{ase2016masud-correct,
	 author = {Rahman, M. M. and Roy, C. K. and Redl, J and Collins, J.},
	 title = {{CORRECT: Code Reviewer Recommendation at GitHub for Vendasta Technologies}},
	 booktitle = {Proc. ASE},
	 year = {2016},
	 pages = {792--797}
}
@inproceedings{ase2016masud,
	 author    = {Rahman, M. M. and Roy, C. K. },
	 title = {{QUICKAR: Automatic Query Reformulation for Concept Location Using Crowdsourced Knowledge}},
	 booktitle = {Proc. ASE},
	 year = {2016},
	 pages = {220--225}
}
@inproceedings{seke2016masud,
	 author    = {Mondal, A. and Rahman, M. M. and Roy, C. K.},
	 title = {{Embedded Emotion-based Classification of Stack Overflow Questions Towards the Question Quality Prediction}},
	 booktitle = {Proc. SEKE},
	 year = {2016},
	 pages = {521-526}
}

2015 (4)
  • Recommending Insightful Comments for Source Code using Crowdsourced Knowledge
    [C11] M. Masudur Rahman, C. K. Roy and Iman Keivanloo. Recommending Insightful Comments for Source Code using Crowdsourced Knowledge. In Proceeding of The 15th IEEE International Working Conference on Source Code Analysis and Manipulation (SCAM 2015), pp. 81--90, Bremen, Germany, September 2015
    Acceptance rate: 35.29%, Reviewed: Single-blind, Download PDF: , Cite this: , Slides: , Replication package:  

  • Recommending Relevant Sections from a Webpage about Programming Errors and Exceptions
    [C10] M. Masudur Rahman and C. K. Roy. Recommending Relevant Sections from a Webpage about Programming Errors and Exceptions. In Proceeding of The 25th Center for Advanced Studies CONference (CASCON 2015), pp. 181--190, Toronto, Canada, November 2015
    Acceptance rate: 29.57%, Reviewed: Single-blind, Download PDF: , Cite this:, Slides: , Replication package:  

  • An Insight into the Unresolved Questions at Stack Overflow
    [C9] M. Masudur Rahman and C. K. Roy. An Insight into the Unresolved Questions at Stack Overflow. In Proceeding of The 12th Working Conference on Mining Software Repositories (MSR 2015), pp. 426--429, Florence, Italy, May 2015
    Reviewed: Single-blind, Download PDF: , Cite this: , Slides: , Replication package:  

  • TextRank Based Search Term Identification for Software Change Tasks
    [C8] M. Masudur Rahman and C. K. Roy. TextRank Based Search Term Identification for Software Change Tasks. In Proceeding of The 22nd IEEE International Conference on Software Analysis, Evolution, and Reengineering (SANER 2015), pp. 540--544, Montreal, Canada, March 2015
    Reviewed: Single-blind, Download PDF: , Cite this: , Slides: , Replication package:  
@INPROCEEDINGS{scam2015masud,
	author={Rahman, M. M. and Roy, C. K. and Keivanloo, I.},
	booktitle={Proc. SCAM},
	title={Recommending {I}nsightful {C}omments for {S}ource {C}ode using {C}rowdsourced {K}nowledge},
	year={2015},
	pages={81-90}
}
@inproceedings{cascon2015masud,
	 author = {Rahman, Mohammad Masudur and Roy, Chanchal K.},
	 title = {Recommending Relevant Sections from a Webpage About Programming Errors and Exceptions},
	 booktitle = {Proc. CASCON},
	 year = {2015},
	 pages = {181--190}
}
@INPROCEEDINGS{msrch2015masud,
	author={M. M. Rahman and C. K. Roy},
	booktitle={ Proc. MSR},
	title={An Insight into the Unresolved Questions at Stack Overflow},
	year={2015},
	pages={426-429}
}
@INPROCEEDINGS{saner2015masud,
	author={Mohammad Masudur Rahman and C. K. Roy},
	booktitle={Proc. SANER},
	title={TextRank based search term identification for software change tasks},
	year={2015},
	pages={540-544}
}

2014 (4)
  • On the Use of Context in Recommending Exception Handling Code Examples
    [C7] M. Masudur Rahman and C. K. Roy. On the Use of Context in Recommending Exception Handling Code Examples. In Proceeding of The 14th IEEE International Working Conference on Source Code Analysis and Manipulation (SCAM 2014), pp. 285--294, Victoria, Canada, September 2014
    Acceptance rate: 31.7%, Reviewed: Single-blind, Download PDF: , Cite this:) , Slides: , Replication package:  

  • SurfClipse: Context-Aware Meta Search in the IDE
    [C6] M. Masudur Rahman and C. K. Roy. SurfClipse: Context-Aware Meta Search in the IDE. In Proceeding of The 30th International Conference on Software Maintenance and Evolution (Tool Demo Track) (ICSME 2014), pp. 617--620, Victoria, Canada, September 2014
    Reviewed: Single-blind, Download PDF: , Cite this: , Slides: , Replication package:    

  • An Insight into the Pull Requests of GitHub
    [C5] M. Masudur Rahman and C. K. Roy. An Insight into the Pull Requests of GitHub. In Proceeding of The 11th Working Conference on Mining Software Repositories (Challenge Track) (MSR 2014), pp. 364--367, Hyderabad, India, May 2014
    Reviewed: Single-blind, Download PDF: , Cite this: , Slides: , Replication package:  

  • Towards a Context-Aware Meta Search Engine for IDE-Based Recommendation about Programming Errors and Exceptions
    [C4] M. Masudur Rahman, S. Yeasmin and C. K. Roy. Towards a Context-Aware Meta Search Engine for IDE-Based Recommendation about Programming Errors and Exceptions. In Proceeding of the IEEE CSMR-18/WCRE-21 Software Evolution Week (CSMR-WCRE 2014), pp. 194--203, Antwerp, Belgium, February 2014
    Acceptance rate: 31.03%, Reviewed: Single-blind, Download PDF: , Cite this:) , Slides: , Replication package:  
@INPROCEEDINGS{scam2014masud,
	author={M. M. Rahman and C. K. Roy},
	booktitle={Proc. SCAM},
	title={On the Use of Context in Recommending Exception Handling Code Examples},
	year={2014},
	pages={285-294}
}
@INPROCEEDINGS{icsme2014masud,
	author={M. M. Rahman and C. K. Roy},
	booktitle={Proc. ICSME},
	title={SurfClipse: Context-Aware Meta-search in the IDE},
	year={2014},
	pages={617-620}
}
@inproceedings{msrch2014masud,
	 author = {Rahman, Mohammad Masudur and Roy, Chanchal K.},
	 title = {An Insight into the Pull Requests of GitHub},
	 booktitle = {Proc. MSR},
	 pages = {364--367}
}
@INPROCEEDINGS{csmrwcre2014masud,
	author={M. M. Rahman and S. Yeasmin and C. K. Roy},
	booktitle={Proc. CSMR-WCRE},
	title={Towards a context-aware IDE-based meta search engine for recommendation about programming errors and exceptions},
	year={2014},
	pages={194-203}
}

2013 (1)
  • An IDE-Based Context-Aware Meta Search Engine
    [C3] M. Masudur Rahman, Shamima Yeasmin Mukta, C. K. Roy. An IDE-Based Context-Aware Meta Search Engine. In Proceedings of Early Reseach Acheivement (ERA) Track of the 20th Working Conference on Reverse Engineering (WCRE 2013), Koblenz, Germany, October 2013, pp. 467--471
    Reviewed: Single-blind, Download PDF: , Cite this: , Slides: , Replication package:  

2010 (1)

2009 (1)

Theses
Traditional code search engines (e.g., Krugle) often do not perform well with natural language queries. They mostly apply keyword matching between query and source code. Hence, they need carefully designed queries containing references to relevant APIs for the code search. Unfortunately, preparing an effective search query is not only challenging but also time-consuming for the developers according to existing studies. In this article, we propose a novel query reformulation technique�RACK�that suggests a list of relevant API classes for a natural language query intended for code search. Our technique offers such suggestions by exploiting keyword-API associations from the questions and answers of Stack Overflow (i.e., crowdsourced knowledge). We first motivate our idea using an exploratory study with 19 standard Java API packages and 344K Java related posts from Stack Overflow. Experiments using 175 code search queries randomly chosen from three Java tutorial sites show that our technique recommends correct API classes within the Top-10 results for 83% of the queries, with 46% mean average precision and 54% recall, which are 66%, 79% and 87% higher respectively than that of the state-of-the-art. Reformulations using our suggested API classes improve 64% of the natural language queries and their overall accuracy improves by 19%. Comparisons with three state-of-the-art techniques demonstrate that RACK outperforms them in the query reformulation by a statistically significant margin. Investigation using three web/code search engines shows that our technique can significantly improve their results in the context of code search.

Posters
  • Sigma Jahan, Mehil Shah, and M. Masudur Rahman. Towards Understanding the Challenges of Bug Localization in Deep Learning Systems, SEMLA 2024, Montreal, Canada.
  • Mehil Shah, M. Masudur Rahman, and Foutse Khomh. Towards Enhancing the Reproducibility of Deep Learning Bugs: An Empirical Study, SEMLA 2024, Montreal, Canada.
  • M. Masudur Rahman and C. K. Roy. Improving Bug Localization with Report Quality Dynamics and Query Reformulation, ICSE 2018, Gothenburg, Sweden.
  • M. Masudur Rahman and C. K. Roy. Improved Query Reformulation for Concept Location using CodeRank and Document Structures, Research Fest 2017, University of Saskatchewan.
  • M. Masudur Rahman, C. K. Roy, Jesse Redl, and Jason Collins. CORRECT: Code Reviewer Recommendation at GitHub for Vendasta Technologies, ASE 2016, Singapore.
  • M. Masudur Rahman and Chanchal Roy. Recommending Relevant Sections from a Webpage about Programming Errors and Exceptions, CSER 2015, Markham, ON, Canada.

Technical Reports (Non-Peer Reviewed)

Publication Stats
  • ICSE (A*) x 6
  • FSE (A*) x 1
  • TOSEM (A*) x 1
  • ASE (A*) x 3
  • EMSE (A) x 6
  • ICSME (A) x 6
  • MSR (A) x 10
  • SANER (A) x 10
  • ICPC (A) x 1
  • JSS (A) x 1
  • SCAM x 3
  • SEKE x 1
  • Learn more on ranking

Award Overview
  • Research Grants Grant X 10
  • Distinguished Reviewer Best Reviewer X 2
  • Gold Medal Gold Medal X 2
  • Best Graduate Thesis Best Thesis X 2
  • Distinguished Paper Best Paper X 2
  • Best Graduate Student Best Student X 1
  • Check out all awards & grants
Copyright © Mohammad Masudur Rahman. Last updated on October 25, 2024

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