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ORCIDTim Menzies
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- affiliation: North Carolina State University, North Carolina, USA
- affiliation (former): University of British Columbia, Vancouver, Canada
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2020 – today
- 2023
[j146]Maria Teresa Baldassarre, Neil A. Ernst, Ben Hermann
, Tim Menzies, Rahul Yedida:
(Re)Use of Research Results (Is Rampant). Commun. ACM 66(2): 75-81 (2023)- [j145]Kewen Peng, Christian Kaltenecker, Norbert Siegmund, Sven Apel, Tim Menzies:
VEER: enhancing the interpretability of model-based optimizations. Empir. Softw. Eng. 28(3): 61 (2023) - [j144]Rahul Yedida, Rahul Krishna, Anup K. Kalia, Tim Menzies, Jin Xiao, Maja Vukovic:
An expert system for redesigning software for cloud applications. Expert Syst. Appl. 219: 119673 (2023) - [j143]Tim Menzies, Brittany Johnson, David L. Roberts, Lauren Alvarez:
The Engineering Mindset Is an Ethical Mindset (We Just Don't Teach It That Way... Yet). IEEE Softw. 40(2): 103-110 (2023) - [j142]Lauren Alvarez, Tim Menzies:
Don't Lie to Me: Avoiding Malicious Explanations With STEALTH. IEEE Softw. 40(3): 43-53 (2023) - [j141]Tim Menzies:
How to "Sell" Ethics (Using AI): An Interview With Alexander Serebrenik. IEEE Softw. 40(3): 95-97 (2023) - [j140]Tim Menzies, Chris Hazard:
"The Best Data Are Fake Data?": An Interview With Chris Hazard. IEEE Softw. 40(5): 121-124 (2023) - [j139]N. C. Shrikanth, Tim Menzies:
Assessing the Early Bird Heuristic (for Predicting Project Quality). ACM Trans. Softw. Eng. Methodol. 32(5): 116:1-116:39 (2023) - [j138]Suvodeep Majumder, Joymallya Chakraborty, Gina R. Bai, Kathryn T. Stolee, Tim Menzies:
Fair Enough: Searching for Sufficient Measures of Fairness. ACM Trans. Softw. Eng. Methodol. 32(6): 134:1-134:22 (2023) - [j137]George Mathew, Amritanshu Agrawal, Tim Menzies:
Finding Trends in Software Research. IEEE Trans. Software Eng. 49(4): 1397-1410 (2023) - [j136]Kewen Peng, Joymallya Chakraborty, Tim Menzies:
FairMask: Better Fairness via Model-Based Rebalancing of Protected Attributes. IEEE Trans. Software Eng. 49(4): 2426-2439 (2023) - [j135]Rahul Yedida, Hong Jin Kang, Huy Tu, Xueqi Yang, David Lo, Tim Menzies:
How to Find Actionable Static Analysis Warnings: A Case Study With FindBugs. IEEE Trans. Software Eng. 49(4): 2856-2872 (2023) - [j134]Xiao Ling, Tim Menzies:
What Not to Test (For Cyber-Physical Systems). IEEE Trans. Software Eng. 49(7): 3811-3826 (2023) - [d2]Tim Menzies:
4src/fish: another release to make zenodo to index this site. Version v0.8.0. Zenodo, 2023 [all versions]
- [d1]Tim Menzies:
4src/fish: another release to make zenodo to index this site. Version v0.9.01. Zenodo, 2023 [all versions] - [i114]Andre Lustosa, Tim Menzies:
Optimizing Predictions for Very Small Data Sets: a case study on Open-Source Project Health Prediction. CoRR abs/2301.06577 (2023) - [i113]Lauren Alvarez, Tim Menzies:
Don't Lie to Me: Avoiding Malicious Explanations with STEALTH. CoRR abs/2301.10407 (2023) - [i112]Huy Tu, Tim Menzies:
Less, but Stronger: On the Value of Strong Heuristics in Semi-supervised Learning for Software Analytics. CoRR abs/2302.01997 (2023) - [i111]Xiao Ling, Tim Menzies:
On the Benefits of Semi-Supervised Test Case Generation for Cyber-Physical Systems. CoRR abs/2305.03714 (2023) - [i110]Tim Menzies:
Model Review: A PROMISEing Opportunity. CoRR abs/2309.01314 (2023) - [i109]Xueqi Yang, Mariusz Jakubowski, Kelly Kang, Haojie Yu, Tim Menzies:
SparseCoder: Advancing Source Code Analysis with Sparse Attention and Learned Token Pruning. CoRR abs/2310.07109 (2023) - [i108]Andre Lustosa, Tim Menzies:
Partial Orderings as Heuristic for Multi-Objective Model-Based Reasoning. CoRR abs/2310.19125 (2023) - 2022
- [j133]Atif Mashkoor, Tim Menzies, Alexander Egyed, Rudolf Ramler:
Artificial Intelligence and Software Engineering: Are We Ready? Computer 55(3): 24-28 (2022) - [j132]Rui Shu, Tianpei Xia, Laurie A. Williams, Tim Menzies:
Omni: automated ensemble with unexpected models against adversarial evasion attack. Empir. Softw. Eng. 27(1): 26 (2022) - [j131]Suvodeep Majumder, Pranav Mody, Tim Menzies:
Revisiting process versus product metrics: a large scale analysis. Empir. Softw. Eng. 27(3): 60 (2022) - [j130]Huy Tu, Tim Menzies:
DebtFree: minimizing labeling cost in self-admitted technical debt identification using semi-supervised learning. Empir. Softw. Eng. 27(4): 80 (2022) - [j129]Tianpei Xia, Wei Fu, Rui Shu, Rishabh Agrawal, Tim Menzies:
Predicting health indicators for open source projects (using hyperparameter optimization). Empir. Softw. Eng. 27(6): 122 (2022) - [j128]Sarah Elder, Nusrat Zahan, Rui Shu, Monica Metro, Valeri Kozarev, Tim Menzies, Laurie A. Williams:
Do I really need all this work to find vulnerabilities? Empir. Softw. Eng. 27(6): 154 (2022) - [j127]Zhe Yu, Jeffrey C. Carver, Gregg Rothermel, Tim Menzies:
Assessing expert system-assisted literature reviews with a case study. Expert Syst. Appl. 200: 116958 (2022) - [j126]Nelly Bencomo, Jin L. C. Guo, Rachel Harrison, Hans-Martin Heyn, Tim Menzies:
The Secret to Better AI and Better Software (Is Requirements Engineering). IEEE Softw. 39(1): 105-110 (2022) - [j125]Huy Tu, Zhe Yu, Tim Menzies:
Better Data Labelling With EMBLEM (and how that Impacts Defect Prediction). IEEE Trans. Software Eng. 48(2): 278-294 (2022) - [j124]Zhe Yu, Fahmid Morshed Fahid, Huy Tu, Tim Menzies:
Identifying Self-Admitted Technical Debts With Jitterbug: A Two-Step Approach. IEEE Trans. Software Eng. 48(5): 1676-1691 (2022) - [j123]Tianpei Xia, Rui Shu, Xipeng Shen, Tim Menzies:
Sequential Model Optimization for Software Effort Estimation. IEEE Trans. Software Eng. 48(6): 1994-2009 (2022) - [j122]Kewen Peng, Tim Menzies:
Defect Reduction Planning (Using TimeLIME). IEEE Trans. Software Eng. 48(7): 2510-2525 (2022) - [j121]Xiao Ling, Rishabh Agrawal, Tim Menzies:
How Different is Test Case Prioritization for Open and Closed Source Projects? IEEE Trans. Software Eng. 48(7): 2526-2540 (2022) - [j120]Amritanshu Agrawal, Xueqi Yang, Rishabh Agrawal, Rahul Yedida, Xipeng Shen, Tim Menzies:
Simpler Hyperparameter Optimization for Software Analytics: Why, How, When? IEEE Trans. Software Eng. 48(8): 2939-2954 (2022) - [j119]Rahul Yedida, Tim Menzies:
On the Value of Oversampling for Deep Learning in Software Defect Prediction. IEEE Trans. Software Eng. 48(8): 3103-3116 (2022) - [c166]Rui Shu, Tianpei Xia, Laurie A. Williams, Tim Menzies:
Dazzle: Using Optimized Generative Adversarial Networks to Address Security Data Class Imbalance Issue. MSR 2022: 144-155 - [c165]Rahul Yedida, Tim Menzies:
How to Improve Deep Learning for Software Analytics (a case study with code smell detection). MSR 2022: 156-166 - [c164]Suvodeep Majumder, Tianpei Xia, Rahul Krishna, Tim Menzies:
Methods for Stabilizing Models Across Large Samples of Projects (with case studies on Predicting Defect and Project Health). MSR 2022: 566-578 - [i107]Huy Tu, Tim Menzies:
DebtFree: Minimizing Labeling Cost in Self-Admitted Technical Debt Identification using Semi-Supervised Learning. CoRR abs/2201.10592 (2022) - [i106]Rahul Yedida, Tim Menzies:
How to Improve Deep Learning for Software Analytics (a case study with code smell detection). CoRR abs/2202.01322 (2022) - [i105]Rui Shu, Tianpei Xia, Laurie A. Williams, Tim Menzies:
Dazzle: Using Optimized Generative Adversarial Networks to Address Security Data Class Imbalance Issue. CoRR abs/2203.11410 (2022) - [i104]Rui Shu, Tianpei Xia, Huy Tu, Laurie A. Williams, Tim Menzies:
Reducing the Cost of Training Security Classifier (via Optimized Semi-Supervised Learning). CoRR abs/2205.00665 (2022) - [i103]Rahul Yedida, Hong Jin Kang, Huy Tu, Xueqi Yang, David Lo, Tim Menzies:
How to Find Actionable Static Analysis Warnings. CoRR abs/2205.10504 (2022) - [i102]Sarah Elder, Nusrat Zahan, Rui Shu, Monica Metro, Valeri Kozarev, Tim Menzies, Laurie A. Williams:
Do I really need all this work to find vulnerabilities? An empirical case study comparing vulnerability detection techniques on a Java application. CoRR abs/2208.01595 (2022) - [i101]Suvodeep Majumder, Joymallya Chakraborty, Tim Menzies:
When Less is More: On the Value of "Co-training" for Semi-Supervised Software Defect Predictors. CoRR abs/2211.05920 (2022) - [i100]Guanqin Zhang, Jiankun Sun, Feng Xu, H. M. N. Dilum Bandara, Shiping Chen, Yulei Sui, Tim Menzies:
A Tale of Two Cities: Data and Configuration Variances in Robust Deep Learning. CoRR abs/2211.10012 (2022) - 2021
- [j118]Rui Shu, Tianpei Xia, Jianfeng Chen, Laurie A. Williams, Tim Menzies:
How to Better Distinguish Security Bug Reports (Using Dual Hyperparameter Optimization). Empir. Softw. Eng. 26(3): 53 (2021) - [j117]Xueqi Yang, Jianfeng Chen, Rahul Yedida, Zhe Yu, Tim Menzies:
Learning to recognize actionable static code warnings (is intrinsically easy). Empir. Softw. Eng. 26(3): 56 (2021) - [j116]N. C. Shrikanth, William Nichols, Fahmid Morshed Fahid, Tim Menzies:
Assessing practitioner beliefs about software engineering. Empir. Softw. Eng. 26(4): 73 (2021) - [j115]Xueqi Yang, Zhe Yu, Junjie Wang, Tim Menzies:
Understanding static code warnings: An incremental AI approach. Expert Syst. Appl. 167: 114134 (2021) - [j114]Tim Menzies:
Shockingly Simple: "KEYS" for Better AI for SE. IEEE Softw. 38(2): 114-118 (2021) - [j113]Junjie Wang, Song Wang, Jianfeng Chen, Tim Menzies, Qiang Cui, Miao Xie, Qing Wang:
Characterizing Crowds to Better Optimize Worker Recommendation in Crowdsourced Testing. IEEE Trans. Software Eng. 47(6): 1259-1276 (2021) - [j112]Amritanshu Agrawal, Wei Fu, Di Chen, Xipeng Shen, Tim Menzies:
How to "DODGE" Complex Software Analytics. IEEE Trans. Software Eng. 47(10): 2182-2194 (2021) - [j111]Zhe Yu, Christopher Theisen, Laurie A. Williams, Tim Menzies:
Improving Vulnerability Inspection Efficiency Using Active Learning. IEEE Trans. Software Eng. 47(11): 2401-2420 (2021) - [j110]Rahul Krishna, Vivek Nair, Pooyan Jamshidi, Tim Menzies:
Whence to Learn? Transferring Knowledge in Configurable Systems Using BEETLE. IEEE Trans. Software Eng. 47(12): 2956-2972 (2021) - [c163]Sarah Elder, Nusrat Zahan, Valeri Kozarev, Rui Shu, Tim Menzies, Laurie A. Williams:
Structuring a Comprehensive Software Security Course Around the OWASP Application Security Verification Standard. ICSE (SEET) 2021: 95-104 - [c162]N. C. Shrikanth, Suvodeep Majumder, Tim Menzies:
Early Life Cycle Software Defect Prediction. Why? How? ICSE 2021: 448-459 - [c161]Tim Menzies, Kewen Peng, Andre Lustosa:
Fairer Software Made Easier (using "Keys"). ASE Workshops 2021: 108-113 - [c160]Huy Tu, Tim Menzies:
FRUGAL: Unlocking Semi-Supervised Learning for Software Analytics. ASE 2021: 394-406 - [c159]Rahul Yedida, Rahul Krishna, Anup K. Kalia, Tim Menzies, Jin Xiao, Maja Vukovic:
Lessons learned from hyper-parameter tuning for microservice candidate identification. ASE 2021: 1141-1145 - [c158]Huy Tu, George Papadimitriou, Mariam Kiran, Cong Wang, Anirban Mandal, Ewa Deelman, Tim Menzies:
Mining Workflows for Anomalous Data Transfers. MSR 2021: 1-12 - [c157]Joymallya Chakraborty, Suvodeep Majumder, Tim Menzies:
Bias in machine learning software: why? how? what to do? ESEC/SIGSOFT FSE 2021: 429-440 - [c156]Rahul Yedida, Tim Menzies:
Documenting evidence of a reuse of 'a systematic study of the class imbalance problem in convolutional neural networks'. ESEC/SIGSOFT FSE 2021: 1595 - [c155]Rahul Yedida, Tim Menzies:
Documenting evidence of a reuse of 'on the number of linear regions of deep neural networks'. ESEC/SIGSOFT FSE 2021: 1596 - [c154]Andre Lustosa, Tim Menzies:
Documenting evidence of a reuse of 'a systematic literature review of techniques and metrics to reduce the cost of mutation testing'. ESEC/SIGSOFT FSE 2021: 1597 - [c153]Andre Lustosa, Tim Menzies:
Documenting evidence of a reuse of 'RefactoringMiner 2.0'. ESEC/SIGSOFT FSE 2021: 1598 - [c152]Kewen Peng, Tim Menzies:
Documenting evidence of a reuse of 'what is a feature? a qualitative study of features in industrial software product lines'. ESEC/SIGSOFT FSE 2021: 1599 - [c151]Kewen Peng, Tim Menzies:
Documenting evidence of a reuse of '"why should I trust you?": explaining the predictions of any classifier'. ESEC/SIGSOFT FSE 2021: 1600 - [c150]Xueqi Yang, Tim Menzies:
Documenting evidence of a replication of 'populating a release history database from version control and bug tracking systems'. ESEC/SIGSOFT FSE 2021: 1601 - [c149]Xueqi Yang, Tim Menzies:
Documenting evidence of a replication of 'analyze this! 145 questions for data scientists in software engineering'. ESEC/SIGSOFT FSE 2021: 1602 - [c148]Xueqi Yang, Tim Menzies:
Documenting evidence of a reproduction of 'is there a "golden" feature set for static warning identification? - an experimental evaluation'. ESEC/SIGSOFT FSE 2021: 1603 - [i99]Jianfeng Chen, Xipeng Shen, Tim Menzies:
Faster SAT Solving for Software with Repeated Structures (with Case Studies on Software Test Suite Minimization). CoRR abs/2101.02817 (2021) - [i98]Rahul Yedida, Xueqi Yang, Tim Menzies:
When SIMPLE is better than complex: A case study on deep learning for predicting Bugzilla issue close time. CoRR abs/2101.06319 (2021) - [i97]Sarah Elder, Nusrat Zahan, Val Kozarev, Rui Shu, Tim Menzies, Laurie A. Williams:
Structuring a Comprehensive Software Security Course Around the OWASP Application Security Verification Standard. CoRR abs/2103.05088 (2021) - [i96]Huy Tu, George Papadimitriou, Mariam Kiran, Cong Wang, Anirban Mandal, Ewa Deelman, Tim Menzies:
Mining Scientific Workflows for Anomalous Data Transfers. CoRR abs/2103.12221 (2021) - [i95]N. C. Shrikanth, Tim Menzies:
The Early Bird Catches the Worm: Better Early Life Cycle Defect Predictors. CoRR abs/2105.11082 (2021) - [i94]Joymallya Chakraborty, Suvodeep Majumder, Tim Menzies:
Bias in Machine Learning Software: Why? How? What to do? CoRR abs/2105.12195 (2021) - [i93]Kewen Peng, Christian Kaltenecker, Norbert Siegmund, Sven Apel, Tim Menzies:
VEER: Disagreement-Free Multi-objective Configuration. CoRR abs/2106.02716 (2021) - [i92]Rahul Yedida, Rahul Krishna, Anup K. Kalia, Tim Menzies, Jin Xiao, Maja Vukovic:
Lessons learned from hyper-parameter tuning for microservice candidate identification. CoRR abs/2106.06652 (2021) - [i91]Tim Menzies, Kewen Peng, Andre Lustosa:
Fairer Software Made Easier (using "Keys"). CoRR abs/2107.05088 (2021) - [i90]Maria Teresa Baldassarre, Neil A. Ernst, Ben Hermann, Tim Menzies, Rahul Yedida:
Crowdsourcing the State of the Art(ifacts). CoRR abs/2108.06821 (2021) - [i89]Huy Tu, Tim Menzies:
FRUGAL: Unlocking SSL for Software Analytics. CoRR abs/2108.09847 (2021) - [i88]Rahul Yedida, Rahul Krishna, Anup K. Kalia, Tim Menzies, Jin Xiao, Maja Vukovic:
Partitioning Cloud-based Microservices (via Deep Learning). CoRR abs/2109.14569 (2021) - [i87]Kewen Peng, Joymallya Chakraborty, Tim Menzies:
xFAIR: Better Fairness via Model-based Rebalancing of Protected Attributes. CoRR abs/2110.01109 (2021) - [i86]Mehdi Bahrami, N. C. Shrikanth, Shade Ruangwan, Lei Liu, Yuji Mizobuchi, Masahiro Fukuyori, Wei-Peng Chen, Kazuki Munakata, Tim Menzies:
PyTorrent: A Python Library Corpus for Large-scale Language Models. CoRR abs/2110.01710 (2021) - [i85]Suvodeep Majumder, Joymallya Chakraborty, Gina R. Bai, Kathryn T. Stolee, Tim Menzies:
Fair Enough: Searching for Sufficient Measures of Fairness. CoRR abs/2110.13029 (2021) - [i84]Joymallya Chakraborty, Huy Tu, Suvodeep Majumder, Tim Menzies:
Can We Achieve Fairness Using Semi-Supervised Learning? CoRR abs/2111.02038 (2021) - [i83]Xiao Ling, Tim Menzies:
Faster Multi-Goal Simulation-Based Testing Using DoLesS (Domination with Least Square Approximation). CoRR abs/2112.01598 (2021) - 2020
- [j109]Amritanshu Agrawal, Tim Menzies, Leandro L. Minku, Markus Wagner, Zhe Yu:
Better software analytics via "DUO": Data mining algorithms using/used-by optimizers. Empir. Softw. Eng. 25(3): 2099-2136 (2020) - [j108]Rahul Krishna, Tim Menzies:
Learning actionable analytics from multiple software projects. Empir. Softw. Eng. 25(5): 3468-3500 (2020) - [j107]Tim Menzies:
The Five Laws of SE for AI. IEEE Softw. 37(1): 81-85 (2020) - [j106]Anita D. Carleton, Erin Harper, Tim Menzies, Tao Xie, Sigrid Eldh, Michael R. Lyu:
The AI Effect: Working at the Intersection of AI and SE. IEEE Softw. 37(4): 26-35 (2020) - [j105]Anita D. Carleton, Erin Harper, Michael R. Lyu, Sigrid Eldh, Tao Xie, Tim Menzies:
Expert Perspectives on AI. IEEE Softw. 37(4): 87-94 (2020) - [j104]Junjie Wang, Ye Yang, Tim Menzies, Qing Wang:
iSENSE2.0: Improving Completion-aware Crowdtesting Management with Duplicate Tagger and Sanity Checker. ACM Trans. Softw. Eng. Methodol. 29(4): 24:1-24:27 (2020) - [j103]Vivek Nair, Zhe Yu, Tim Menzies, Norbert Siegmund, Sven Apel:
Finding Faster Configurations Using FLASH. IEEE Trans. Software Eng. 46(7): 794-811 (2020) - [c147]N. C. Shrikanth, Tim Menzies:
Assessing practitioner beliefs about software defect prediction. ICSE (SEIP) 2020: 182-190 - [c146]N. C. Shrikanth, Tim Menzies:
What disconnects practitioner belief and empirical evidence? ICSE (Companion Volume) 2020: 286-287 - [c145]Joymallya Chakraborty, Kewen Peng, Tim Menzies:
Making Fair ML Software using Trustworthy Explanation. ASE 2020: 1229-1233 - [c144]Joymallya Chakraborty, Suvodeep Majumder, Zhe Yu, Tim Menzies:
Fairway: a way to build fair ML software. ESEC/SIGSOFT FSE 2020: 654-665 - [e11]Leandro L. Minku, Tim Menzies, Meiyappan Nagappan:
PROMISE '20: 16th International Conference on Predictive Models and Data Analytics in Software Engineering, Virtual Event, USA, November 8-9, 2020. ACM 2020, ISBN 978-1-4503-8127-7 [contents] - [i82]Zhe Yu, Fahmid Morshed Fahid, Huy Tu, Tim Menzies:
Identifying Self-Admitted Technical Debts with Jitterbug: A Two-step Approach. CoRR abs/2002.11049 (2020) - [i81]Huy Tu, Rishabh Agrawal, Tim Menzies:
The Changing Nature of Computational Science Software. CoRR abs/2003.05922 (2020) - [i80]Kewen Peng, Tim Menzies:
How to Improve AI Tools (by Adding in SE Knowledge): Experiments with the TimeLIME Defect Reduction Tool. CoRR abs/2003.06887 (2020) - [i79]Joymallya Chakraborty, Suvodeep Majumder, Zhe Wu, Tim Menzies:
Fairway: SE Principles for Building Fairer Software. CoRR abs/2003.10354 (2020) - [i78]Xueqi Yang, Jianfeng Chen, Rahul Yedida, Zhe Yu, Tim Menzies:
How to Recognize Actionable Static Code Warnings (Using Linear SVMs). CoRR abs/2006.00444 (2020) - [i77]N. C. Shrikanth, William Nichols, Fahmid Morshed Fahid, Tim Menzies:
Assessing Practitioner Beliefs about Software Engineering. CoRR abs/2006.05060 (2020) - [i76]Tianpei Xia, Wei Fu, Rui Shu, Tim Menzies:
Predicting Project Health for Open Source Projects (using the DECART Hyperparameter Optimizer). CoRR abs/2006.07240 (2020) - [i75]Kewen Peng, Tim Menzies:
Defect Reduction Planning (using TimeLIME). CoRR abs/2006.07416 (2020) - [i74]Joymallya Chakraborty, Kewen Peng, Tim Menzies:
Making Fair ML Software using Trustworthy Explanation. CoRR abs/2007.02893 (2020) - [i73]Xiao Ling, Rishabh Agrawal, Tim Menzies:
How Different is Test Case Prioritization for Open and Closed Source Projects? CoRR abs/2008.00612 (2020) - [i72]Rahul Yedida, Tim Menzies:
Improving Deep Learning for Defect Prediction (using the GHOST Hyperparameter Optimizer). CoRR abs/2008.03835 (2020) - [i71]Suvodeep Majumder, Pranav Mody, Tim Menzies:
Revisiting Process versus Product Metrics: a Large Scale Analysis. CoRR abs/2008.09569 (2020) - [i70]