|
Research Publications
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journal article |
|
conference paper |
|
dissertation |
|
poster |
|
technical report |
Journals
- Towards Enhancing the
Reproducibility of Deep Learning Bugs: An Empirical
Study
[J8]
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:
- 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:
-
Works for Me! Cannot Reproduce
-- A Large Scale Empirical Study of Non-reproducible Bugs
[J6] M. Masudur Rahman, F.
Khomh, and M. Castelluccio. Works for Me! Cannot Reproduce -- A Large
Scale Empirical Study of Non-reproducible Bugs. Journal of Empirical
Software Engineering (EMSE), pp. 44 (To appear)
Impact Factor = 3.48, Download
PDF: , Cite this: ,
Replication package:
-
The Forgotten Role of Search
Queries in IR-based Bug Localization: An Empirical Study
[J5] 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 (To appear)
Impact Factor = 3.48, Download
PDF: , Cite this: ,
Replication package:
-
Automatic Query
Reformulation for Code Search using Crowdsourced Knowledge
[J4] 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 = 3.48, Download
PDF: , Cite this:
,
Replication package:
- The Reproducibility of
Programming-Related Issues in Stack Overflow
Questions
[J3]
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:
- Improved Retrieval
of Programming Solutions With Code Examples Using a
Multi-featured Score.
[J2]
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:
- CROKAGE:
Effective Solution Recommendations for Programming Tasks by
Leveraging Crowd Knowledge
[J1]
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),
pp. 25:4707--4758, June 2020
Impact Factor = 3.48, Download
PDF: , Cite
this: , Replication package:
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)
-
Works for Me! Cannot Reproduce
-- A Large Scale Empirical Study of Non-reproducible Bugs
[J6] M. Masudur Rahman, F.
Khomh, and M. Castelluccio. Works for Me! Cannot Reproduce -- A Large
Scale Empirical Study of Non-reproducible Bugs. Journal of Empirical
Software Engineering (EMSE), pp. 44 (To appear)
Impact Factor = 3.48, Download
PDF: , Cite this: ,
Replication package:
-
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. [ICSE 2022(A*) Journal First Track]
Impact Factor = 3.48, Download
PDF: , Cite this: ,
Replication package:
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{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)
-
Why are Some Bugs
Non-Reproducible? An Empirical Investigation using Data
Fusion
[C31]
M. Masudur Rahman, Foutse Khomh, and Marco Castelluccio. Why are
Some Bugs Non-Reproducible? An Empirical Investigation using Data
Fusion. In Proceeding of The 36th International Conference on Software
Maintenance and Evolution (ICSME 2020), pp. 12,
Adelaide, Australia, September, 2020 (To appear) [TCSE Distinguished Paper Award 2020*]
Acceptance rate: 24.90%,
Reviewed: Double-blind, Download PDF: , Cite this: ,
Slides: , Replication package:
- 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:
-
Effective Reformulation of
Query for Code Search using Crowdsourced Knowledge and
Extra-Large Data Analytics
[C24]
M. Masudur Rahman and C. K. Roy. Effective
Reformulation of Query for Code Search using Crowdsourced Knowledge and
Extra-Large Data Analytics. In Proceeding of The 34th International
Conference on Software Maintenance and Evolution (ICSME 2018), pp. 516--527,
Madrid, Spain, September, 2018 (to appear) [TCSE
Distinguished Paper Award 2018 Nomination*]
Acceptance rate: 21%, 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}
}
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,
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{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:
@INPROCEEDINGS{wcre2013masud,
author={M. M. Rahman and S. Yeasmin and C. K. Roy},
booktitle={Proc. WCRE},
title={An IDE-based context-aware meta search engine},
year={2013},
pages={467-471}
}
@PhDThesis{Rahman:Thesis:2019,
author = {Mohammad Masudur Rahman},
title = {{Supporting Source Code Search with Context-Aware and Semantics-Driven Query Reformulation}},
school = {University of Saskatchewan},
address = {Canada},
year = {2019}
}
@MastersThesis{Rahman:Thesis:2014,
author = {Mohammad Masudur Rahman},
title = {{Exploiting Context in Dealing with Programming Errors and Exceptions in the IDE}},
school = {University of Saskatchewan},
address = {Canada},
year = {2014}
}
@MastersThesis{Rahman:Thesis:2009,
author = {Mohammad Masudur Rahman},
title = {{Information Retrieval by Modified Term Weighting Method using Random Walk Model with Query Term Position Ranking}},
school = {Khulna University},
address = {Bangladesh},
year = {2009}
}
@INPROCEEDINGS{icsps2009masud,
author={A. S. M. Arif and M. M. Rahman and S. Y. Mukta},
booktitle={Proc. ICSPS},
title={Information Retrieval by Modified Term Weighting Method Using Random Walk Model with Query Term Position Ranking},
year={2009},
pages={526-530}
}
@INPROCEEDINGS{vsmm2010hafiz,
author={H. {Rahaman} and M. M. {Rashid} and M. {Rahman}},
booktitle={Proc. VSMM},
title={Heritage interpretation: Collective reconstruction of Sompur Mahavihara, Bangladesh},
year={2010},
pages={163-170}
}
Theses
-
Supporting
Source Code Search with Context-Aware and Semantics-Driven Query
Reformulation
PhD: Mohammad Masudur Rahman, Supporting Source Code
Search with Context-Aware and Semantics-Driven Query Reformulation, PhD
Dissertation, University of Saskatchewan, 2019
[Best PhD Thesis 2019 (CS)*, U of S Doctoral Thesis Award 2019*, 2020 WAGS/ProQuest Innovation in Technology Award
Nomination]
Download PDF: , Cite
this: ,
Replication package:
-
Exploiting
Context in Dealing with Programming Errors and Exceptions in the
IDE
MSc: Mohammad Masudur Rahman, Exploiting Context in
Dealing with Programming Errors and Exceptions in the IDE, MSc Thesis,
University of Saskatchewan, 2014
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this: ,
Replication package:
-
Information Retrieval by
Modified Term Weighting Method using Random Walk Model with
Query Term Position Ranking
B.Sc: Md. Masudur Rahman, Shamima Yeasmin, Information
Retrieval by Modified Term Weighting Method using Random Walk Model with
Query Term Position Ranking, BSc Thesis, Khulna University, 2009
Download PDF: , Cite
this:
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)
-
Subjective
Evaluation of Software Quality Using Crowdsource Knowledge: An
Exploratory Study
[TR2]
M. M. Rahman, C.K. Roy, I. Keivanloo. Subjective
Evaluation of Software Quality Using Crowdsource Knowledge: An
Exploratory Study. Technical Report, Department of Computer Science,
University of Saskatchewan, 10 pp, 2013. Download PDF:
-
Adaptive
Bug Classification for CVE List using Bayesian Probabilistic
Approach
[TR1]
M. M. Rahman, Shamima Yeasmin. Adaptive Bug
Classification for CVE List using Bayesian Probabilistic Approach.
Technical Report, Department of Computer Science, University of
Saskatchewan, 10 pp, 2013. Download PDF:
|
Masud's Links
Useful Links
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
- Grant X 10
- Best Reviewer X 2
- Gold Medal X 2
- Best Thesis X 2
- Best Paper X 2
- Best Student X 1
- Check out all awards & grants
|