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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
- 2024
[j162]Xiao Ling
, Tim Menzies, Christopher J. Hazard, Jack Shu, Jacob Beel:
Trading Off Scalability, Privacy, and Performance in Data Synthesis. IEEE Access 12: 26642-26654 (2024)- [j161]Andre Lustosa, Tim Menzies:
iSNEAK: Partial Ordering as Heuristics for Model- Based Reasoning in Software Engineering. IEEE Access 12: 142915-142929 (2024) - [j160]Suvodeep Majumder, Joymallya Chakraborty, Tim Menzies:
When less is more: on the value of "co-training" for semi-supervised software defect predictors. Empir. Softw. Eng. 29(2): 51 (2024) - [j159]Tim Menzies:
A brief note, with thanks, on the contributions of Guenther Ruhe. Inf. Softw. Technol. 173: 107486 (2024) - [j158]Tim Menzies, Bowen Xu, Hong Jin Kang, Jie M. Zhang, Jiri Gesi, Sagar Sen, Beatriz Cassoli, Nicolas Jourdan, Jieke Shi, Phu Hong Nguyen, Valentina Golendukhina:
SEA4DQ 2024 Workshop Summary. ACM SIGSOFT Softw. Eng. Notes 49(4): 29-30 (2024) - [j157]Brittany Johnson, Tim Menzies:
Ethics: Why Software Engineers Can't Afford to Look Away. IEEE Softw. 41(1): 142-144 (2024) - [j156]Brittany Johnson, Tim Menzies:
Fighting for What's Right: An Interview With Marc Canellas. IEEE Softw. 41(2): 104-107 (2024) - [j155]Brittany Johnson, Tim Menzies:
The Power of Positionality - Why Accessibility? An Interview With Kevin Moran and Arun Krishnavajjala. IEEE Softw. 41(3): 91-94 (2024) - [j154]Brittany Johnson, Tim Menzies:
Are You Trapped in the Configuration Abyss? An Interview With Prof. Sven Apel. IEEE Softw. 41(4): 175-181 (2024) - [j153]Tim Menzies, Brittany Johnson:
Powering Down: An Interview With Federica Sarro on Tackling Energy Consumption in AI-Powered Software Systems. IEEE Softw. 41(5): 89-92 (2024) - [j152]Brittany Johnson, Tim Menzies:
AI Over-Hype: A Dangerous Threat (and How to Fix It). IEEE Softw. 41(6): 131-138 (2024) - [j151]Andre Lustosa, Tim Menzies:
Learning from Very Little Data: On the Value of Landscape Analysis for Predicting Software Project Health. ACM Trans. Softw. Eng. Methodol. 33(3): 58:1-58:22 (2024) - [j150]Zhe Yu, Joymallya Chakraborty, Tim Menzies:
FairBalance: How to Achieve Equalized Odds With Data Pre-Processing. IEEE Trans. Software Eng. 50(9): 2294-2312 (2024) - [j149]Sebastián Uchitel, Marsha Chechik, Massimiliano Di Penta, Bram Adams, Nazareno Aguirre, Gabriele Bavota, Domenico Bianculli, Kelly Blincoe, Ana Cavalcanti, Yvonne Dittrich, Filomena Ferrucci, Rashina Hoda, LiGuo Huang, David Lo, Michael R. Lyu, Lei Ma, Jonathan I. Maletic, Leonardo Mariani, Collin McMillan, Tim Menzies, Martin Monperrus, Ana Moreno, Nachiappan Nagappan, Liliana Pasquale, Patrizio Pelliccione, Michael Pradel, Rahul Purandare, Sukyoung Ryu, Mehrdad Sabetzadeh, Alexander Serebrenik, Jun Sun, Chakkrit Kla Tantithamthavorn, Christoph Treude, Manuel Wimmer, Yingfei Xiong, Tao Yue, Andy Zaidman, Tao Zhang, Hao Zhong:
Scoping Software Engineering for AI: The TSE Perspective. IEEE Trans. Software Eng. 50(11): 2709-2711 (2024) - [e12]Tim Menzies, Bowen Xu, Hong Jin Kang, Jie M. Zhang:
Proceedings of the 4th International Workshop on Software Engineering and AI for Data Quality in Cyber-Physical Systems/Internet of Things, SEA4DQ 2024, Porto de Galinhas, Brazil, 15 July 2024. ACM 2024 [contents] - [i118]Md. Rayhanur Rahman, Brandon Wroblewski, Quinn Matthews, Brantley Morgan, Tim Menzies, Laurie A. Williams:
Mining Temporal Attack Patterns from Cyberthreat Intelligence Reports. CoRR abs/2401.01883 (2024) - [i117]Rahul Yedida, Tim Menzies:
SMOOTHIE: A Theory of Hyper-parameter Optimization for Software Analytics. CoRR abs/2401.09622 (2024) - [i116]Tim Menzies, Andre Lustosa:
Streamlining Software Reviews: Efficient Predictive Modeling with Minimal Examples. CoRR abs/2405.12920 (2024) - 2023
- [j148]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) - [j147]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) - [j146]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) - [j145]Guanqin Zhang, Jiankun Sun, Feng Xu, Yulei Sui, H. M. N. Dilum Bandara, Shiping Chen, Tim Menzies:
A Tale of Two Cities: Data and Configuration Variances in Robust Deep Learning. IEEE Internet Comput. 27(6): 13-20 (2023) - [j144]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) - [j143]Lauren Alvarez, Tim Menzies:
Don't Lie to Me: Avoiding Malicious Explanations With STEALTH. IEEE Softw. 40(3): 43-53 (2023) - [j142]Tim Menzies:
How to "Sell" Ethics (Using AI): An Interview With Alexander Serebrenik. IEEE Softw. 40(3): 95-97 (2023) - [j141]Tim Menzies, Chris Hazard:
"The Best Data Are Fake Data?": An Interview With Chris Hazard. IEEE Softw. 40(5): 121-124 (2023) - [j140]Brittany Johnson, Tim Menzies:
Unfairness Is Everywhere, so What to Do? An Interview With Jeanna Matthews. IEEE Softw. 40(6): 135-138 (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) - [c167]Tim Menzies:
Model Review: A PROMISEing Opportunity. PROMISE 2023: 64-68 - [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] - [i115]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) - [i114]Lauren Alvarez, Tim Menzies:
Don't Lie to Me: Avoiding Malicious Explanations with STEALTH. CoRR abs/2301.10407 (2023) - [i113]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) - [i112]Xiao Ling, Tim Menzies:
On the Benefits of Semi-Supervised Test Case Generation for Cyber-Physical Systems. CoRR abs/2305.03714 (2023) - [i111]Tim Menzies:
Model Review: A PROMISEing Opportunity. CoRR abs/2309.01314 (2023) - [i110]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) - [i109]Andre Lustosa, Tim Menzies:
Partial Orderings as Heuristic for Multi-Objective Model-Based Reasoning. CoRR abs/2310.19125 (2023) - [i108]Xiao Ling, Tim Menzies, Christopher J. Hazard, Jack Shu, Jacob Beel:
Trading Off Scalability, Privacy, and Performance in Data Synthesis. CoRR abs/2312.05436 (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]Rui Shu, Tianpei Xia, Laurie A. Williams, Tim Menzies:
Omni: Automated Ensemble with Unexpected Models against Adversarial Evasion Attack. CoRR abs/2011.12720 (2020) - [i69]N. C. Shrikanth, Suvodeep Majumder, Tim Menzies:
Early Life Cycle Software Defect Prediction. Why? How? CoRR abs/2011.13071 (2020)
2010 – 2019
- 2019
- [j102]Zhe Yu, Tim Menzies:
FAST2: An intelligent assistant for finding relevant papers. Expert Syst. Appl. 120: 57-71 (2019) - [j101]Junjie Wang, Mingyang Li, Song Wang, Tim Menzies, Qing Wang:
Images don't lie: Duplicate crowdtesting reports detection with screenshot information. Inf. Softw. Technol. 110: 139-155 (2019) - [j100]Tim Menzies, Martin J. Shepperd:
"Bad smells" in software analytics papers. Inf. Softw. Technol. 112: 35-47 (2019) - [j99]Jianfeng Chen, Vivek Nair, Rahul Krishna, Tim Menzies:
"Sampling" as a Baseline Optimizer for Search-Based Software Engineering. IEEE Trans. Software Eng. 45(6): 597-614 (2019) - [j98]Morakot Choetkiertikul, Hoa Khanh Dam, Truyen Tran, Trang Pham, Aditya Ghose, Tim Menzies:
A Deep Learning Model for Estimating Story Points. IEEE Trans. Software Eng. 45(7): 637-656 (2019) - [j97]Rahul Krishna, Tim Menzies:
Bellwethers: A Baseline Method for Transfer Learning. IEEE Trans. Software Eng. 45(11): 1081-1105 (2019) - [c143]Tim Menzies:
Take control: on the unreasonable effectiveness of software analytics. ICSE (SEIP) 2019: 265-266 - [c142]Junjie Wang, Ye Yang, Rahul Krishna, Tim Menzies, Qing Wang:
iSENSE: completion-aware crowdtesting management. ICSE 2019: 912-923 - [c141]Di Chen, Kathryn T. Stolee, Tim Menzies:
Replication can improve prior results: a GitHub study of pull request acceptance. ICPC 2019: 179-190 - [c140]Zhe Yu, Fahmid M. Fahid, Tim Menzies, Gregg Rothermel, Kyle Patrick, Snehit Cherian:
TERMINATOR: better automated UI test case prioritization. ESEC/SIGSOFT FSE 2019: 883-894 - [c139]Jianfeng Chen, Joymallya Chakraborty, Philip Clark, Kevin Haverlock, Snehit Cherian, Tim Menzies:
Predicting breakdowns in cloud services (with SPIKE). ESEC/SIGSOFT FSE 2019: 916-924 - [e10]Tim Menzies, Burak Turhan:
Proceedings of the 7th International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering, RAISE@ICSE 2019, Montreal, QC, Canada, May 28, 2019. IEEE / ACM 2019, ISBN 978-1-7281-2272-4 [contents] - [i68]Amritanshu Agrawal, Wei Fu, Di Chen, Xipeng Shen, Tim Menzies:
How to "DODGE" Complex Software Analytics? CoRR abs/1902.01838 (2019) - [i67]Di Chen, Kathryn T. Stolee, Tim Menzies:
Replication Can Improve Prior Results: A GitHub Study of Pull Request Acceptance. CoRR abs/1902.04060 (2019) - [i66]N. C. Shrikanth, Tim Menzies:
Assessing Developer Beliefs: A Reply to "Perceptions, Expectations, and Challenges in Defect Prediction". CoRR abs/1904.05794 (2019) - [i65]Suvodeep Majumder, Joymallya Chakraborty, Amritanshu Agrawal, Tim Menzies:
Why Software Projects need Heroes (Lessons Learned from 1100+ Projects). CoRR abs/1904.09954 (2019) - [i64]Huy Tu, Tim Menzies:
Enhanced Labeling of Issue Reports (with F3T). CoRR abs/1905.01719 (2019) - [i63]Jianfeng Chen, Tim Menzies:
Faster Creation of Smaller Test Suites (with SNAP). CoRR abs/1905.05358 (2019) - [i62]Joymallya Chakraborty, Tianpei Xia, Fahmid M. Fahid, Tim Menzies:
Software Engineering for Fairness: A Case Study with Hyperparameter Optimization. CoRR abs/1905.05786 (2019) - [i61]Jianfeng Chen, Joymallya Chakraborty, Philip Clark, Kevin Haverlock, Snehit Cherian, Tim Menzies:
Predicting Breakdowns in Cloud Services (with SPIKE). CoRR abs/1905.06390 (2019) - [i60]Rui Shu, Tianpei Xia, Laurie A. Williams, Tim Menzies:
Better Security Bug Report Classification via Hyperparameter Optimization. CoRR abs/1905.06872 (2019) - [i59]Zhe Yu, Fahmid M. Fahid, Tim Menzies, Gregg Rothermel, Kyle Patrick, Snehit Cherian:
TERMINATOR: Better Automated UI Test Case Prioritization. CoRR abs/1905.07019 (2019) - [i58]Fahmid M. Fahid, Zhe Yu, Tim Menzies:
Better Technical Debt Detection via SURVEYing. CoRR abs/1905.08297 (2019) - [i57]Zhe Yu, Jeffrey C. Carver, Gregg Rothermel, Tim Menzies:
Searching for Better Test Case Prioritization Schemes: a Case Study of AI-assisted Systematic Literature Review. CoRR abs/1909.07249 (2019) - [i56]Xueqi Yang, Zhe Yu, Junjie Wang, Tim Menzies:
An Expert System for Learning Software Engineering Knowledge (with Case Studies in Understanding Static Code Warning). CoRR abs/1911.01387 (2019) - [i55]Rahul Krishna, Vivek Nair, Pooyan Jamshidi, Tim Menzies:
Whence to Learn? Transferring Knowledge in Configurable Systems using BEETLE. CoRR abs/1911.01817 (2019) - [i54]Rui Shu, Tianpei Xia, Jianfeng Chen, Laurie A. Williams, Tim Menzies:
Improved Recognition of Security Bugs via Dual Hyperparameter Optimization. CoRR abs/1911.02476 (2019) - [i53]Suvodeep Majumder, Rahul Krishna, Tim Menzies:
Learning GENERAL Principles from Hundreds of Software Projects. CoRR abs/1911.04250 (2019) - [i52]Amritanshu Agrawal, Tim Menzies:
Is AI different for SE? CoRR abs/1912.04061 (2019) - [i51]Tianpei Xia, Jianfeng Chen, Rui Shu, Tim Menzies:
Sequential Model Optimization for Software Process Control. CoRR abs/1912.04189 (2019) - [i50]N. C. Shrikanth, Tim Menzies:
Assessing Practitioner Beliefs. CoRR abs/1912.10093 (2019) - 2018
- [j96]Vivek Nair, Tim Menzies, Norbert Siegmund, Sven Apel:
Faster discovery of faster system configurations with spectral learning. Autom. Softw. Eng. 25(2): 247-277 (2018) - [j95]Zhe Yu, Nicholas A. Kraft, Tim Menzies:
Finding better active learners for faster literature reviews. Empir. Softw. Eng. 23(6): 3161-3186 (2018) - [j94]Jianfeng Chen, Vivek Nair, Tim Menzies:
Beyond evolutionary algorithms for search-based software engineering. Inf. Softw. Technol. 95: 281-294 (2018) - [j93]Amritanshu Agrawal, Wei Fu, Tim Menzies:
What is wrong with topic modeling? And how to fix it using search-based software engineering. Inf. Softw. Technol. 98: 74-88 (2018) - [j92]Justyna Petke, Tim Menzies:
Guest Editorial for the Special Section from the 9th International Symposium on Search Based Software Engineering. Inf. Softw. Technol. 104: 194 (2018) - [j91]Rafael Prikladnicki, Tim Menzies:
From Voice of Evidence to Redirections. IEEE Softw. 35(1): 11-13 (2018) - [j90]Ye Yang, Davide Falessi, Tim Menzies, Jairus Hihn:
Actionable Analytics for Software Engineering. IEEE Softw. 35(1): 51-53 (2018) - [j89]Tim Menzies:
The Unreasonable Effectiveness of Software Analytics. IEEE Softw. 35(2): 96-98 (2018) - [j88]Tim Menzies, Thomas Zimmermann:
Software Analytics: What's Next? IEEE Softw. 35(5): 64-70 (2018) - [j87]George Mathew, Tim Menzies:
Software Engineering's Top Topics, Trends, and Researchers. IEEE Softw. 35(5): 88-93 (2018) - [j86]Jaechang Nam, Wei Fu, Sunghun Kim, Tim Menzies, Lin Tan:
Heterogeneous Defect Prediction. IEEE Trans. Software Eng. 44(9): 874-896 (2018) - [c138]Jianfeng Chen, Tim Menzies:
RIOT: A Stochastic-Based Method for Workflow Scheduling in the Cloud. IEEE CLOUD 2018: 318-325 - [c137]Chin-Jung Hsu, Vivek Nair, Tim Menzies, Vincent W. Freeh:
Micky: A Cheaper Alternative for Selecting Cloud Instances. IEEE CLOUD 2018: 409-416 - [c136]Tim Menzies:
Introduction to the Minitrack on Frontiers in AI and Software Engineering. HICSS 2018: 1 - [c135]Chin-Jung Hsu, Vivek Nair, Vincent W. Freeh, Tim Menzies:
Arrow: Low-Level Augmented Bayesian Optimization for Finding the Best Cloud VM. ICDCS 2018: 660-670 - [c134]Amritanshu Agrawal, Akond Rahman, Rahul Krishna, Alexander Sobran, Tim Menzies:
We don't need another hero?: the impact of "heroes" on software development. ICSE (SEIP) 2018: 245-253 - [c133]Rahul Krishna, Amritanshu Agrawal, Akond Rahman, Alexander Sobran, Tim Menzies:
What is the connection between issues, bugs, and enhancements?: lessons learned from 800+ software projects. ICSE (SEIP) 2018: 306-315 - [c132]Amritanshu Agrawal, Tim Menzies:
Is "better data" better than "better data miners"?: on the benefits of tuning SMOTE for defect prediction. ICSE 2018: 1050-1061 - [c131]Vivek Nair, Amritanshu Agrawal, Jianfeng Chen, Wei Fu, George Mathew, Tim Menzies, Leandro L. Minku, Markus Wagner, Zhe Yu:
Data-driven search-based software engineering. MSR 2018: 341-352 - [c130]Suvodeep Majumder, Nikhila Balaji, Katie Brey, Wei Fu, Tim Menzies:
500+ times faster than deep learning: a case study exploring faster methods for text mining stackoverflow. MSR 2018: 554-563 - [c129]Zhe Yu, Tim Menzies:
Total recall, language processing, and software engineering. NL4SE@ESEC/SIGSOFT FSE 2018: 10-13 - [c128]Di Chen, Wei Fu, Rahul Krishna, Tim Menzies:
Applications of psychological science for actionable analytics. ESEC/SIGSOFT FSE 2018: 456-467 - [e9]Olga Baysal, Tim Menzies:
Proceedings of the 4th ACM SIGSOFT International Workshop on Software Analytics, SWAN@ESEC/SIGSOFT FSE 2018, Lake Buena Vista, FL, USA, November 5, 2018. ACM 2018, ISBN 978-1-4503-6056-2 [contents] - [i49]Vivek Nair, Zhe Yu, Tim Menzies, Norbert Siegmund, Sven Apel:
Finding Faster Configurations using FLASH. CoRR abs/1801.02175 (2018) - [i48]Vivek Nair, Amritanshu Agrawal, Jianfeng Chen, Wei Fu, George Mathew, Tim Menzies, Leandro L. Minku, Markus Wagner, Zhe Yu:
Data-Driven Search-based Software Engineering. CoRR abs/1801.10241 (2018) - [i47]Suvodeep Majumder, Nikhila Balaji, Katie Brey, Wei Fu, Tim Menzies:
500+ Times Faster Than Deep Learning (A Case Study Exploring Faster Methods for Text Mining StackOverflow). CoRR abs/1802.05319 (2018) - [i46]Chin-Jung Hsu, Vivek Nair, Tim Menzies, Vincent W. Freeh:
Scout: An Experienced Guide to Find the Best Cloud Configuration. CoRR abs/1803.01296 (2018) - [i45]Vivek Nair, Rahul Krishna, Tim Menzies, Pooyan Jamshidi:
Transfer Learning with Bellwethers to find Good Configurations. CoRR abs/1803.03900 (2018) - [i44]Wei Fu, Tim Menzies, Di Chen, Amritanshu Agrawal:
Building Better Quality Predictors Using "ε-Dominance". CoRR abs/1803.04608 (2018) - [i43]Di Chen, Wei Fu, Rahul Krishna, Tim Menzies:
Applications of Psychological Science for Actionable Analytics. CoRR abs/1803.05067 (2018) - [i42]Rahul Krishna, Suvodeep Majumder, Tim Menzies, Martin J. Shepperd:
Bad Smells in Software Analytics Papers. CoRR abs/1803.05518 (2018) - [i41]Chin-Jung Hsu, Vivek Nair, Tim Menzies, Vincent W. Freeh:
Micky: A Cheaper Alternative for Selecting Cloud Instances. CoRR abs/1803.05587 (2018) - [i40]Zhe Yu, Christopher Theisen, Hyunwoo Sohn, Laurie A. Williams, Tim Menzies:
Cost-aware Vulnerability Prediction: the HARMLESS Approach. CoRR abs/1803.06545 (2018) - [i39]Tianpei Xia, Jianfeng Chen, George Mathew, Xipeng Shen, Tim Menzies:
Why Software Effort Estimation Needs SBSE. CoRR abs/1804.00626 (2018) - [i38]Amritanshu Agrawal, Huy Tu, Tim Menzies:
Can You Explain That, Better? Comprehensible Text Analytics for SE Applications. CoRR abs/1804.10657 (2018) - [i37]Tianpei Xia, Rahul Krishna, Jianfeng Chen, George Mathew, Xipeng Shen, Tim Menzies:
Hyperparameter Optimization for Effort Estimation. CoRR abs/1805.00336 (2018) - [i36]Junjie Wang, Ye Yang, Rahul Krishna, Tim Menzies, Qing Wang:
Effective Automated Decision Support for Managing Crowdtesting. CoRR abs/1805.02744 (2018) - [i35]Junjie Wang, Mingyang Li, Song Wang, Tim Menzies, Qing Wang:
Cutting Away the Confusion From Crowdtesting. CoRR abs/1805.02763 (2018) - [i34]Junjie Wang, Ye Yang, Zhe Yu, Tim Menzies, Qing Wang:
Crowdtesting : When is The Party Over? CoRR abs/1805.03218 (2018) - [i33]George Mathew, Tim Menzies:
Better Metrics for Ranking SE Researchers. CoRR abs/1805.12124 (2018) - [i32]Zhe Yu, Tim Menzies:
Total Recall, Language Processing, and Software Engineering. CoRR abs/1809.00039 (2018) - [i31]Amritanshu Agrawal, Tim Menzies, Leandro L. Minku, Markus Wagner, Zhe Yu:
Better Software Analytics via "DUO": Data Mining Algorithms Using/Used-by Optimizers. CoRR abs/1812.01550 (2018) - 2017
- [j85]Marouane Kessentini, Tim Menzies:
A guest editorial: special issue on search based software engineering and data mining. Autom. Softw. Eng. 24(3): 573-574 (2017) - [j84]Tim Menzies, William Nichols, Forrest Shull, Lucas Layman:
Are delayed issues harder to resolve? Revisiting cost-to-fix of defects throughout the lifecycle. Empir. Softw. Eng. 22(4): 1903-1935 (2017) - [j83]Tim Menzies, Ye Yang, George Mathew, Barry W. Boehm, Jairus Hihn:
Negative results for software effort estimation. Empir. Softw. Eng. 22(5): 2658-2683 (2017) - [j82]Rahul Krishna, Tim Menzies, Lucas Layman:
Less is more: Minimizing code reorganization using XTREE. Inf. Softw. Technol. 88: 53-66 (2017) - [j81]Rahul Pandita, Raoul Jetley, Sithu D. Sudarsan, Tim Menzies, Laurie A. Williams:
TMAP: Discovering relevant API methods through text mining of API documentation. J. Softw. Evol. Process. 29(12) (2017) - [c127]Zhe Yu, Tim Menzies:
Data Balancing for Technologically Assisted Reviews: Undersampling or Reweighting. CLEF (Working Notes) 2017 - [c126]Neil A. Ernst, John Klein, George Mathew, Tim Menzies:
Using Stakeholder Preferences to Make Better Architecture Decisions. ICSA Workshops 2017: 133-136 - [c125]George Mathew, Amritanshu Agrawal, Tim Menzies:
Trends in topics at SE conferences (1993-2013). ICSE (Companion Volume) 2017: 397-398 - [c124]George Mathew, Tim Menzies, Neil A. Ernst, John Klein:
"SHORT"er Reasoning About Larger Requirements Models. RE 2017: 154-163 - [c123]Wei Fu, Tim Menzies:
Easy over hard: a case study on deep learning. ESEC/SIGSOFT FSE 2017: 49-60 - [c122]Wei Fu, Tim Menzies:
Revisiting unsupervised learning for defect prediction. ESEC/SIGSOFT FSE 2017: 72-83 - [c121]Vivek Nair, Tim Menzies, Norbert Siegmund, Sven Apel:
Using bad learners to find good configurations. ESEC/SIGSOFT FSE 2017: 257-267 - [e8]Olga Baysal, Tim Menzies:
Proceedings of the 3rd ACM SIGSOFT International Workshop on Software Analytics, SWAN@ESEC/SIGSOFT FSE 2017, Paderborn, Germany, September 4, 2017. ACM 2017, ISBN 978-1-4503-5157-7 [contents] - [e7]Tim Menzies, Justyna Petke:
Search Based Software Engineering - 9th International Symposium, SSBSE 2017, Paderborn, Germany, September 9-11, 2017, Proceedings. Lecture Notes in Computer Science 10452, Springer 2017, ISBN 978-3-319-66298-5 [contents] - [i30]Jianfeng Chen, Vivek Nair, Tim Menzies:
Beyond Evolutionary Algorithms for Search-based Software Engineering. CoRR abs/1701.07950 (2017) - [i29]Vivek Nair, Tim Menzies, Norbert Siegmund, Sven Apel:
Faster Discovery of Faster System Configurations with Spectral Learning. CoRR abs/1701.08106 (2017) - [i28]George Mathew, Tim Menzies, Neil A. Ernst, John Klein:
Shorter Reasoning About Larger Requirements Models. CoRR abs/1702.05568 (2017) - [i27]Vivek Nair, Tim Menzies, Norbert Siegmund, Sven Apel:
Using Bad Learners to find Good Configurations. CoRR abs/1702.05701 (2017) - [i26]Mitch Rees-Jones, Matthew Martin, Tim Menzies:
Better Predictors for Issue Lifetime. CoRR abs/1702.07735 (2017) - [i25]Di Chen, Kathryn T. Stolee, Tim Menzies:
Replicating and Scaling up Qualitative Analysis using Crowdsourcing: A Github-based Case Study. CoRR abs/1702.08571 (2017) - [i24]Wei Fu, Tim Menzies:
Revisiting Unsupervised Learning for Defect Prediction. CoRR abs/1703.00132 (2017) - [i23]Wei Fu, Tim Menzies:
Easy over Hard: A Case Study on Deep Learning. CoRR abs/1703.00133 (2017) - [i22]Rahul Krishna, Tim Menzies:
Simpler Transfer Learning (Using "Bellwethers"). CoRR abs/1703.06218 (2017) - [i21]Amritanshu Agrawal, Tim Menzies:
"Better Data" is Better than "Better Data Miners" (Benefits of Tuning SMOTE for Defect Prediction). CoRR abs/1705.03697 (2017) - [i20]Vivek Nair, Zhe Yu, Tim Menzies:
FLASH: A Faster Optimizer for SBSE Tasks. CoRR abs/1705.05018 (2017) - [i19]Zhe Yu, Tim Menzies:
Testing Reading Tactics for Automated Reading Assistance: Is it Useful to Apply Old Knowledge? CoRR abs/1705.05420 (2017) - [i18]Rahul Krishna, Tim Menzies:
Learning Effective Changes For Software Projects. CoRR abs/1708.05442 (2017) - [i17]Jianfeng Chen, Tim Menzies:
RIOT: a Novel Stochastic Method for Rapidly Configuring Cloud-Based Workflows. CoRR abs/1708.08127 (2017) - [i16]Rahul Krishna, Amritanshu Agrawal, Akond Rahman, Alexander Sobran, Tim Menzies:
What is the Connection Between Issues, Bugs, and Enhancements? (Lessons Learned from 800+ Software Projects). CoRR abs/1710.08736 (2017) - [i15]Amritanshu Agrawal, Akond Rahman, Rahul Krishna, Alexander Sobran, Tim Menzies:
We Don't Need Another Hero? The Impact of "Heroes" on Software Development. CoRR abs/1710.09055 (2017) - [i14]Akond Rahman, Amritanshu Agrawal, Rahul Krishna, Alexander Sobran, Tim Menzies:
Continuous Integration: The Silver Bullet? CoRR abs/1711.03933 (2017) - [i13]Chin-Jung Hsu, Vivek Nair, Vincent W. Freeh, Tim Menzies:
Low-Level Augmented Bayesian Optimization for Finding the Best Cloud VM. CoRR abs/1712.10081 (2017) - 2016
- [j80]Wei Fu, Tim Menzies, Xipeng Shen:
Tuning for software analytics: Is it really necessary? Inf. Softw. Technol. 76: 135-146 (2016) - [j79]Joseph Krall, Tim Menzies, Misty D. Davies:
Learning Mitigations for Pilot Issues When Landing Aircraft (via Multiobjective Optimization and Multiagent Simulations). IEEE Trans. Hum. Mach. Syst. 46(2): 221-230 (2016) - [c120]Tim Menzies:
How not to do it: anti-patterns for data science in software engineering. ICSE (Companion Volume) 2016: 887 - [c119]Rahul Krishna, Tim Menzies, Wei Fu:
Too much automation? the bellwether effect and its implications for transfer learning. ASE 2016: 122-131 - [c118]Lucas Layman, Allen P. Nikora, Joshua Meek, Tim Menzies:
Topic modeling of NASA space system problem reports: research in practice. MSR 2016: 303-314 - [c117]Vivek Nair, Tim Menzies, Jianfeng Chen:
An (Accidental) Exploration of Alternatives to Evolutionary Algorithms for SBSE. SSBSE 2016: 96-111 - [p6]Tim Menzies:
Seven principles of inductive software engineering. Perspectives on Data Science for Software Engineering 2016: 13-17 - [p5]Tim Menzies:
Correlation is not causation (or, when not to scream "Eureka!"). Perspectives on Data Science for Software Engineering 2016: 327-330 - [e6]Tim Menzies, Laurie A. Williams, Thomas Zimmermann:
Perspectives on Data Science for Software Engineering. Academic Press 2016, ISBN 978-0-12-804206-9 [contents] - [i12]Jianfeng Chen, Vivek Nair, Rahul Krishna, Tim Menzies:
Is "Sampling" better than "Evolution" for Search-based Software Engineering? CoRR abs/1608.07617 (2016) - [i11]George Mathew, Amritanshu Agrawal, Tim Menzies:
Trends in Topics at SE Conferences (1993-2013). CoRR abs/1608.08100 (2016) - [i10]Amritanshu Agrawal, Wei Fu, Tim Menzies:
What is Wrong with Topic Modeling? (and How to Fix it Using Search-based SE). CoRR abs/1608.08176 (2016) - [i9]Morakot Choetkiertikul, Hoa Khanh Dam, Truyen Tran, Trang Pham, Aditya Ghose, Tim Menzies:
A deep learning model for estimating story points. CoRR abs/1609.00489 (2016) - [i8]Wei Fu, Tim Menzies, Xipeng Shen:
Tuning for Software Analytics: is it Really Necessary? CoRR abs/1609.01759 (2016) - [i7]Wei Fu, Vivek Nair, Tim Menzies:
Why is Differential Evolution Better than Grid Search for Tuning Defect Predictors? CoRR abs/1609.02613 (2016) - [i6]Rahul Krishna, Tim Menzies, Lucas Layman:
Recommendations for Intelligent Code Reorganization. CoRR abs/1609.03614 (2016) - [i5]Tim Menzies, William Nichols, Forrest Shull, Lucas Layman:
Are Delayed Issues Harder to Resolve? Revisiting Cost-to-Fix of Defects throughout the Lifecycle. CoRR abs/1609.04886 (2016) - [i4]Tim Menzies, Ye Yang, George Mathew, Barry W. Boehm, Jairus Hihn:
Negative Results for Software Effort Estimation. CoRR abs/1609.05563 (2016) - [i3]Zhe Yu, Nicholas A. Kraft, Tim Menzies:
How to Read Less: Better Machine Assisted Reading Methods for Systematic Literature Reviews. CoRR abs/1612.03224 (2016) - [i2]George Mathew, Tim Menzies, Jairus Hihn:
Impacts of Bad ESP (Early Size Predictions) on Software Effort Estimation. CoRR abs/1612.03240 (2016) - 2015
- [j78]Rachel Harrison, Tim Menzies:
Guest editorial: special issue on realizing AI synergies in software engineering. Autom. Softw. Eng. 22(1): 1-2 (2015) - [j77]Rachel Harrison, Tim Menzies:
Guest editorial: special issue on realizing AI synergies in software engineering (part 2). Autom. Softw. Eng. 22(2): 143-144 (2015) - [j76]Tim Menzies, Corina S. Pasareanu:
Guest editorial: special multi-issue on selected topics in Automated Software Engineering. Autom. Softw. Eng. 22(3): 289-290 (2015) - [j75]Tim Menzies, Corina S. Pasareanu:
Guest editorial: special multi-issue on selected topics in automated software engineering. Autom. Softw. Eng. 22(4): 437-438 (2015) - [j74]Tim Menzies:
Cross-Project Data for Software Engineering. Computer 48(12): 6 (2015) - [j73]Ekrem Kocaguneli, Tim Menzies, Emilia Mendes:
Transfer learning in effort estimation. Empir. Softw. Eng. 20(3): 813-843 (2015) - [j72]Joseph Krall, Tim Menzies, Misty D. Davies:
GALE: Geometric Active Learning for Search-Based Software Engineering. IEEE Trans. Software Eng. 41(10): 1001-1018 (2015) - [c116]Fayola Peters, Tim Menzies, Lucas Layman:
LACE2: Better Privacy-Preserving Data Sharing for Cross Project Defect Prediction. ICSE (1) 2015: 801-811 - [c115]Tim Menzies, Leandro L. Minku, Fayola Peters:
The Art and Science of Analyzing Software Data; Quantitative Methods. ICSE (2) 2015: 959-960 - [c114]Luciano Baresi, Tim Menzies, Andreas Metzger, Thomas Zimmermann:
1st International Workshop on Big Data Software Engineering (BIGDSE 2015). ICSE (2) 2015: 965-966 - [c113]Jairus Hihn, Tim Menzies:
Data Mining Methods and Cost Estimation Models: Why is it So Hard to Infuse New Ideas? ASE Workshops 2015: 5-9 - [c112]Rahul Krishna, Tim Menzies:
Actionable = Cluster + Contrast? ASE Workshops 2015: 14-17 - [p4]Christian Bird, Tim Menzies, Thomas Zimmermann:
Past, Present, and Future of Analyzing Software Data. The Art and Science of Analyzing Software Data 2015: 1-13 - [e5]Christian Bird, Tim Menzies, Thomas Zimmermann:
The Art and Science of Analyzing Software Data. Morgan Kaufmann / Elsevier 2015, ISBN 978-0-12-411519-4 [contents] - [e4]Luciano Baresi, Tim Menzies, Andreas Metzger, Thomas Zimmermann:
1st IEEE/ACM International Workshop on Big Data Software Engineering, BIGDSE 2015, Florence, Italy, May 23, 2015. IEEE Computer Society 2015, ISBN 978-1-4673-7025-7 [contents] - 2014
- [j71]Tim Menzies, Marjan Mernik:
Special issue on realizing artificial intelligence synergies in software engineering. Softw. Qual. J. 22(1): 49-50 (2014) - [c111]Joseph Krall, Tim Menzies, Misty D. Davies:
Learning the Task Management Space of an Aircraft Approach Model. AAAI Spring Symposia 2014 - [c110]Tim Menzies, Christian Bird, Thomas Zimmermann:
Analyzing software data: after the gold rush (a goldfish-bowl panel). ICSE Companion 2014: 103-104 - [p3]Tim Menzies:
Occam's Razor and Simple Software Project Management. Software Project Management in a Changing World 2014: 447-472 - [p2]Tim Menzies:
Data Mining. Recommendation Systems in Software Engineering 2014: 39-75 - [i1]Harald C. Gall, Tim Menzies, Laurie A. Williams, Thomas Zimmermann:
Software Development Analytics (Dagstuhl Seminar 14261). Dagstuhl Reports 4(6): 64-83 (2014) - 2013
- [j70]Jacky Keung, Ekrem Kocaguneli, Tim Menzies:
Finding conclusion stability for selecting the best effort predictor in software effort estimation. Autom. Softw. Eng. 20(4): 543-567 (2013) - [j69]Ekrem Kocaguneli, Tim Menzies, Jacky W. Keung:
Kernel methods for software effort estimation - Effects of different kernel functions and bandwidths on estimation accuracy. Empir. Softw. Eng. 18(1): 1-24 (2013) - [j68]Tim Menzies, Günes Koru:
Predictive models in software engineering. Empir. Softw. Eng. 18(3): 433-434 (2013) - [j67]Yue Jiang, Bojan Cukic, Tim Menzies, Jie Lin:
Incremental Development of Fault Prediction Models. Int. J. Softw. Eng. Knowl. Eng. 23(10): 1399-1426 (2013) - [j66]Tim Menzies:
Guest editorial for the Special Section on BEST PAPERS from the 2011 conference on Predictive Models in Software Engineering (PROMISE). Inf. Softw. Technol. 55(8): 1477-1478 (2013) - [j65]Ekrem Kocaguneli, Tim Menzies:
Software effort models should be assessed via leave-one-out validation. J. Syst. Softw. 86(7): 1879-1890 (2013) - [j64]Tim Menzies:
Beyond Data Mining. IEEE Softw. 30(3): 92 (2013) - [j63]Tim Menzies, Thomas Zimmermann:
Software Analytics: So What? IEEE Softw. 30(4): 31-37 (2013) - [j62]Tim Menzies, Thomas Zimmermann:
The Many Faces of Software Analytics. IEEE Softw. 30(5): 28-29 (2013) - [j61]Tim Menzies, Andrew Butcher, David R. Cok, Andrian Marcus, Lucas Layman, Forrest Shull, Burak Turhan, Thomas Zimmermann:
Local versus Global Lessons for Defect Prediction and Effort Estimation. IEEE Trans. Software Eng. 39(6): 822-834 (2013) - [j60]Ekrem Kocaguneli, Tim Menzies, Jacky Keung, David R. Cok, Raymond J. Madachy:
Active Learning and Effort Estimation: Finding the Essential Content of Software Effort Estimation Data. IEEE Trans. Software Eng. 39(8): 1040-1053 (2013) - [j59]Fayola Peters, Tim Menzies, Liang Gong, Hongyu Zhang:
Balancing Privacy and Utility in Cross-Company Defect Prediction. IEEE Trans. Software Eng. 39(8): 1054-1068 (2013) - [j58]Tim Menzies, Adam Brady, Jacky Keung, Jairus Hihn, Steve Williams, Oussama El-Rawas, Phillip Green II, Barry W. Boehm:
Learning Project Management Decisions: A Case Study with Case-Based Reasoning versus Data Farming. IEEE Trans. Software Eng. 39(12): 1698-1713 (2013) - [c109]Zhimin He, Fayola Peters, Tim Menzies, Ye Yang:
Learning from Open-Source Projects: An Empirical Study on Defect Prediction. ESEM 2013: 45-54 - [c108]Abdel Salam Sayyad, Joseph Ingram, Tim Menzies, Hany H. Ammar:
Optimum feature selection in software product lines: Let your model and values guide your search. CMSBSE@ICSE 2013: 22-27 - [c107]Abdel Salam Sayyad, Tim Menzies, Hany H. Ammar:
On the value of user preferences in search-based software engineering: a case study in software product lines. ICSE 2013: 492-501 - [c106]Sonia Haiduc, Gabriele Bavota, Andrian Marcus, Rocco Oliveto, Andrea De Lucia, Tim Menzies:
Automatic query reformulations for text retrieval in software engineering. ICSE 2013: 842-851 - [c105]Ekrem Kocaguneli, Thomas Zimmermann, Christian Bird, Nachiappan Nagappan, Tim Menzies:
Distributed development considered harmful? ICSE 2013: 882-890 - [c104]Tim Menzies, Ekrem Kocaguneli, Fayola Peters, Burak Turhan, Leandro L. Minku:
Data science for software engineering. ICSE 2013: 1484-1486 - [c103]Christian Bird, Tim Menzies, Thomas Zimmermann:
1st international workshop on data analysis patterns in software engineering (DAPSE 2013). ICSE 2013: 1517-1518 - [c102]Rachel Harrison, Sol J. Greenspan, Tim Menzies, Marjan Mernik, Pedro Rangel Henriques, Daniela Carneiro da Cruz, Daniel Rodríguez:
2nd international workshop on realizing artificial intelligence synergies in software engineering (RAISE 2013). ICSE 2013: 1543-1544 - [c101]Christian Bird, Tim Menzies, Thomas Zimmermann:
Foreword. DAPSE@ICSE 2013: iii-iv - [c100]Abdel Salam Sayyad, Joseph Ingram, Tim Menzies, Hany H. Ammar:
Scalable product line configuration: A straw to break the camel's back. ASE 2013: 465-474 - [c99]Giuseppe Scanniello, Carmine Gravino, Andrian Marcus, Tim Menzies:
Class level fault prediction using software clustering. ASE 2013: 640-645 - [c98]Fayola Peters, Tim Menzies, Andrian Marcus:
Better cross company defect prediction. MSR 2013: 409-418 - [c97]Tim Menzies:
Beyond data mining; towards "idea engineering". PROMISE 2013: 11:1-11:6 - [c96]Ekrem Kocaguneli, Bojan Cukic, Tim Menzies, Huihua Lu:
Building a second opinion: learning cross-company data. PROMISE 2013: 12:1-12:10 - 2012
- [j57]Ayse Basar Bener, Tim Menzies:
Guest editorial: learning to organize testing. Autom. Softw. Eng. 19(2): 137-140 (2012) - [j56]Tim Menzies, Martin J. Shepperd:
Special issue on repeatable results in software engineering prediction. Empir. Softw. Eng. 17(1-2): 1-17 (2012) - [j55]Markus Lumpe, Rajesh Vasa, Tim Menzies, Rebecca Rush, Burak Turhan:
Learning Better Inspection Optimization Policies. Int. J. Softw. Eng. Knowl. Eng. 22(5): 621-644 (2012) - [j54]Rachel Harrison, Daniela Carneiro da Cruz, Pedro Rangel Henriques, Maria João Varanda Pereira, Shih-Hsi Liu, Tim Menzies, Marjan Mernik, Daniel Rodríguez:
Report from the first international workshop on realizing artificial intelligence synergies in software engineering (RAISE 2012). ACM SIGSOFT Softw. Eng. Notes 37(5): 34-35 (2012) - [j53]Ekrem Kocaguneli, Tim Menzies, Ayse Bener, Jacky W. Keung:
Exploiting the Essential Assumptions of Analogy-Based Effort Estimation. IEEE Trans. Software Eng. 38(2): 425-438 (2012) - [j52]Ekrem Kocaguneli, Tim Menzies, Jacky W. Keung:
On the Value of Ensemble Effort Estimation. IEEE Trans. Software Eng. 38(6): 1403-1416 (2012) - [c95]Abdel Salam Sayyad, Hany H. Ammar, Tim Menzies:
Software feature model recommendations using data mining. RSSE@ICSE 2012: 47-51 - [c94]Fayola Peters, Tim Menzies:
Privacy and utility for defect prediction: Experiments with MORPH. ICSE 2012: 189-199 - [c93]Tim Menzies, Thomas Zimmermann:
Goldfish bowl panel: Software development analytics. ICSE 2012: 1032-1033 - [c92]Yang Sok Kim, Byeong Ho Kang, Seung Hwan Ryu, Paul Compton, Soyeon Caren Han, Tim Menzies:
Crowd-Sourced Knowledge Bases. PKAW 2012: 258-271 - [c91]Raymond Borges, Tim Menzies:
Learning to change projects. PROMISE 2012: 11-18 - [c90]Ekrem Kocaguneli, Tim Menzies, Jairus Hihn, Byeong Ho Kang:
Size doesn't matter?: on the value of software size features for effort estimation. PROMISE 2012: 89-98 - [e3]Michael Goedicke, Tim Menzies, Motoshi Saeki:
IEEE/ACM International Conference on Automated Software Engineering, ASE'12, Essen, Germany, September 3-7, 2012. ACM 2012, ISBN 978-1-4503-1204-2 [contents] - 2011
- [j51]Ashutosh Nandeshwar, Tim Menzies, Adam Nelson:
Learning patterns of university student retention. Expert Syst. Appl. 38(12): 14984-14996 (2011) - [j50]Topi Haapio, Tim Menzies:
Exploring the Effort of General Software Project Activities with Data Mining. Int. J. Softw. Eng. Knowl. Eng. 21(5): 725-753 (2011) - [j49]Adam Nelson, Tim Menzies, Gregory Gay:
Sharing experiments using open-source software. Softw. Pract. Exp. 41(3): 283-305 (2011) - [j48]James H. Andrews, Tim Menzies, Felix Chun Hang Li:
Genetic Algorithms for Randomized Unit Testing. IEEE Trans. Software Eng. 37(1): 80-94 (2011) - [c89]Ekrem Kocaguneli, Tim Menzies:
How to Find Relevant Data for Effort Estimation? ESEM 2011: 255-264 - [c88]Tim Menzies, Andrew Butcher, Andrian Marcus, Thomas Zimmermann, David R. Cok:
Local vs. global models for effort estimation and defect prediction. ASE 2011: 343-351 - [p1]Tim Menzies, Forrest Shull:
The Quest for Convincing Evidence. Making Software 2011: 3-16 - [e2]Tim Menzies:
Proceedings of the 7th International Conference on Predictive Models in Software Engineering, PROMISE 2011, Banff, Alberta, Canada, September 20-21, 2011. ACM 2011, ISBN 978-1-4503-0709-3 [contents] - 2010
- [j47]Gregory Gay, Tim Menzies, Omid Jalali, Gregory E. Mundy, Beau Gilkerson, Martin S. Feather, James D. Kiper:
Finding robust solutions in requirements models. Autom. Softw. Eng. 17(1): 87-116 (2010) - [j46]Tim Menzies, Zach Milton, Burak Turhan, Bojan Cukic, Yue Jiang, Ayse Basar Bener:
Defect prediction from static code features: current results, limitations, new approaches. Autom. Softw. Eng. 17(4): 375-407 (2010) - [j45]Tim Menzies, Omid Jalali, Jairus Hihn, Daniel Baker, Karen T. Lum:
Stable rankings for different effort models. Autom. Softw. Eng. 17(4): 409-437 (2010) - [j44]Gregory Gay, Tim Menzies, Misty D. Davies, Karen Gundy-Burlet:
Automatically finding the control variables for complex system behavior. Autom. Softw. Eng. 17(4): 439-468 (2010) - [j43]Ayse Tosun, Ayse Basar Bener, Burak Turhan, Tim Menzies:
Practical considerations in deploying statistical methods for defect prediction: A case study within the Turkish telecommunications industry. Inf. Softw. Technol. 52(11): 1242-1257 (2010) - [j42]Oussama El-Rawas, Tim Menzies:
A second look at Faster, Better, Cheaper. Innov. Syst. Softw. Eng. 6(4): 319-335 (2010) - [j41]Adam Brady, Tim Menzies, Oussama El-Rawas, Ekrem Kocaguneli, Jacky W. Keung:
Case-Based Reasoning for Reducing Software Development Effort. J. Softw. Eng. Appl. 3(11): 1005-1014 (2010) - [c87]LiGuo Huang, Daniel Port, Liang Wang, Tao Xie, Tim Menzies:
Text mining in supporting software systems risk assurance. ASE 2010: 163-166 - [c86]Ekrem Kocaguneli, Gregory Gay, Tim Menzies, Ye Yang, Jacky W. Keung:
When to use data from other projects for effort estimation. ASE 2010: 321-324 - [c85]Burak Turhan, Ayse Basar Bener, Tim Menzies:
Regularities in Learning Defect Predictors. PROFES 2010: 116-130 - [c84]Adam Brady, Tim Menzies:
Case-based reasoning vs parametric models for software quality optimization. PROMISE 2010: 3 - [c83]Hongyu Zhang, Adam Nelson, Tim Menzies:
On the value of learning from defect dense components for software defect prediction. PROMISE 2010: 14 - [c82]Earl T. Barr, Christian Bird, Eric Hyatt, Tim Menzies, Gregorio Robles:
On the shoulders of giants. FoSER 2010: 23-28 - [c81]Andrian Marcus, Tim Menzies:
Software is data too. FoSER 2010: 229-232 - [e1]Tim Menzies, Günes Koru:
Proceedings of the 6th International Conference on Predictive Models in Software Engineering, PROMISE 2010, Timisoara, Romania, September 12-13, 2010. ACM 2010, ISBN 978-1-4503-0404-7 [contents]
2000 – 2009
- 2009
- [j40]Letha H. Etzkorn, Tim Menzies:
Special issue on information retrieval for program comprehension. Empir. Softw. Eng. 14(1): 1-4 (2009) - [j39]Burak Turhan, Tim Menzies, Ayse Basar Bener, Justin S. Di Stefano:
On the relative value of cross-company and within-company data for defect prediction. Empir. Softw. Eng. 14(5): 540-578 (2009) - [j38]Tim Menzies, Osamu Mizuno, Yasunari Takagi, Tohru Kikuno:
Explanation vs Performance in Data Mining: A Case Study with Predicting Runaway Projects. J. Softw. Eng. Appl. 2(4): 221-236 (2009) - [j37]Tim Menzies, Steve Williams, Oussama El-Rawas, Daniel Baker, Barry W. Boehm, Jairus Hihn, Karen T. Lum, Raymond J. Madachy:
Accurate estimates without local data? Softw. Process. Improv. Pract. 14(4): 213-225 (2009) - [c80]Topi Haapio, Tim Menzies:
Data mining with software industry project data: A case study. IADIS AC (2) 2009: 33-38 - [c79]Tim Menzies, Steve Williams, Barry W. Boehm, Jairus Hihn:
How to avoid drastic software process change (using stochastic stability). ICSE 2009: 540-550 - [c78]Gregory Gay, Sonia Haiduc, Andrian Marcus, Tim Menzies:
On the use of relevance feedback in IR-based concept location. ICSM 2009: 351-360 - [c77]Andres S. Orrego, Tim Menzies, Oussama El-Rawas:
On the Relative Merits of Software Reuse. ICSP 2009: 186-197 - [c76]Yue Jiang, Jie Lin, Bojan Cukic, Tim Menzies:
Variance Analysis in Software Fault Prediction Models. ISSRE 2009: 99-108 - [c75]Joseph D'Alessandro, Cynthia D. Tanner, Bonnie W. Morris, Tim Menzies:
Is Continuous Compliance Assurance Possible? ITNG 2009: 1599 - [c74]Phillip Green II, Tim Menzies, Steve Williams, Oussama El-Rawas:
Understanding the Value of Software Engineering Technologies. ASE 2009: 52-61 - [c73]Bryan Lemon, Aaron Riesbeck, Tim Menzies, Justin Price, Joseph D'Alessandro, Rikard Carlsson, Tomi Prifiti, Fayola Peters, Huihua Lu, Daniel Port:
Applications of Simulation and AI Search: Assessing the Relative Merits of Agile vs Traditional Software Development. ASE 2009: 580-584 - [c72]Tim Menzies, Oussama El-Rawas, Jairus Hihn, Barry W. Boehm:
Can we build software faster and better and cheaper? PROMISE 2009: 2 - [c71]James H. Andrews, Tim Menzies:
On the value of combining feature subset selection with genetic algorithms: faster learning of coverage models. PROMISE 2009: 13 - [c70]Gregory Gay, Tim Menzies, Bojan Cukic, Burak Turhan:
How to build repeatable experiments. PROMISE 2009: 15 - 2008
- [j36]Tim Menzies:
Editorial, special issue, repeatable experiments in software engineering. Empir. Softw. Eng. 13(5): 469-471 (2008) - [j35]Tim Menzies, Markland Benson, Ken Costello, Christina Moats, Melissa Northey, Julian Richardson:
Learning better IV&V practices. Innov. Syst. Softw. Eng. 4(2): 169-183 (2008) - [j34]Martin S. Feather, Steven L. Cornford, Kenneth A. Hicks, James D. Kiper, Tim Menzies:
A Broad, Quantitative Model for Making Early Requirements Decisions. IEEE Softw. 25(2): 49-56 (2008) - [c69]Gary D. Boetticher, Tim Menzies, Thomas J. Ostrand, Günther Ruhe:
4th international workshop on predictor models in SE (PROMISE 2008). ICSE Companion 2008: 1061-1062 - [c68]Tim Menzies, Andrian Marcus:
Automated severity assessment of software defect reports. ICSM 2008: 346-355 - [c67]Tim Menzies, Oussama El-Rawas, Barry W. Boehm, Raymond J. Madachy, Jairus Hihn, Daniel Baker, Karen T. Lum:
Accurate Estimates without Calibration? ICSP 2008: 210-221 - [c66]Yue Jiang, Bojan Cukic, Tim Menzies:
Cost Curve Evaluation of Fault Prediction Models. ISSRE 2008: 197-206 - [c65]Yue Jiang, Bojan Cukic, Tim Menzies:
Can data transformation help in the detection of fault-prone modules? DEFECTS 2008: 16-20 - [c64]Burak Turhan, Ayse Basar Bener, Tim Menzies:
Nearest neighbor sampling for cross company defect predictors: abstract only. DEFECTS 2008: 26 - [c63]Daniel Port, Alexy Olkov, Tim Menzies:
Using Simulation to Investigate Requirements Prioritization Strategies. ASE 2008: 268-277 - [c62]Johann Schumann, Karen Gundy-Burlet, Corina S. Pasareanu, Tim Menzies, Tony Barrett:
Tool Support for Parametric Analysis of Large Software Simulation Systems. ASE 2008: 497-498 - [c61]Yue Jiang, Bojan Cukic, Tim Menzies, Nick Bartlow:
Comparing design and code metrics for software quality prediction. PROMISE@ICSE 2008: 11-18 - [c60]Tim Menzies, Burak Turhan, Ayse Bener, Gregory Gay, Bojan Cukic, Yue Jiang:
Implications of ceiling effects in defect predictors. PROMISE@ICSE 2008: 47-54 - [c59]Omid Jalali, Tim Menzies, Martin S. Feather:
Optimizing requirements decisions with keys. PROMISE@ICSE 2008: 79-86 - 2007
- [j33]Tim Menzies, David Owen, Julian Richardson:
The Strangest Thing About Software. Computer 40(1): 54-60 (2007) - [j32]Tim Menzies, Jeremy Greenwald, Art Frank:
Data Mining Static Code Attributes to Learn Defect Predictors. IEEE Trans. Software Eng. 33(1): 2-13 (2007) - [j31]Tim Menzies, Alex Dekhtyar, Justin S. Di Stefano, Jeremy Greenwald:
Problems with Precision: A Response to "Comments on 'Data Mining Static Code Attributes to Learn Defect Predictors'". IEEE Trans. Software Eng. 33(9): 637-640 (2007) - [c58]Yue Jiang, Bojan Cukic, Tim Menzies:
Fault Prediction using Early Lifecycle Data. ISSRE 2007: 237-246 - [c57]James H. Andrews, Felix Chun Hang Li, Tim Menzies:
Nighthawk: a two-level genetic-random unit test data generator. ASE 2007: 144-153 - [c56]Tim Menzies, Oussama El-Rawas, Jairus Hihn, Martin S. Feather, Raymond J. Madachy, Barry W. Boehm:
The business case for automated software engineering. ASE 2007: 303-312 - [c55]Omid Jalali, Tim Menzies, Daniel Baker, Jairus Hihn:
Column Pruning Beats Stratification in Effort Estimation. PROMISE@ICSE 2007: 7 - 2006
- [j30]Tim Menzies, Ying Hu:
Just enough learning (of association rules): the TAR2 "Treatment" learner. Artif. Intell. Rev. 25(3): 211-229 (2006) - [j29]Tim Menzies, Julian Richardson:
Making Sense of Requirements, Sooner. Computer 39(10): 112-114 (2006) - [j28]Tim Menzies, Jairus Hihn:
Evidence-Based Cost Estimation for Better-Quality Software. IEEE Softw. 23(4): 64-66 (2006) - [j27]Tim Menzies, Zhihao Chen, Jairus Hihn, Karen T. Lum:
Selecting Best Practices for Effort Estimation. IEEE Trans. Software Eng. 32(11): 883-895 (2006) - [c54]Jimin Gao, Mats Per Erik Heimdahl, David Owen, Tim Menzies:
On the Distribution of Property Violations in Formal Models: An Initial Study. COMPSAC (1) 2006: 150-160 - [c53]Marcus S. Fisher, Tim Menzies:
Learning IV&V Strategies. HICSS 2006 - [c52]Tim Menzies, Julian Richardson:
Qualitative Modeling for Requirements Engineering. SEW 2006: 11-20 - 2005
- [j26]Tim Menzies, Charles Pecheur:
Verification and Validation and Artificial Intelligence. Adv. Comput. 65: 154-203 (2005) - [j25]Zhihao Chen, Tim Menzies, Daniel Port, Barry W. Boehm:
Feature subset selection can improve software cost estimation accuracy. ACM SIGSOFT Softw. Eng. Notes 30(4): 1-6 (2005) - [j24]Tim Menzies, Daniel Port, Zhihao Chen, Jairus Hihn:
Simple software cost analysis: safe or unsafe? ACM SIGSOFT Softw. Eng. Notes 30(4): 1-6 (2005) - [j23]Zhihao Chen, Barry W. Boehm, Tim Menzies, Daniel Port:
Finding the Right Data for Software Cost Modeling. IEEE Softw. 22(6): 38-46 (2005) - [c51]Tim Menzies, Daniel Port, Zhihao Chen, Jairus Hihn, Sherry Stukes:
Validation methods for calibrating software effort models. ICSE 2005: 587-595 - [c50]Jelber Sayyad-Shirabad, Tim Menzies:
Predictor models in software engineering (PROMISE). ICSE 2005: 692 - [c49]Tim Menzies, Daniel Port, Zhihao Chen, Jairus Hihn:
Specialization and extrapolation of software cost models. ASE 2005: 384-387 - [c48]Tim Menzies, Dan Port, Zhihao Chen, Jairus Hihn:
Simple software cost analysis: safe or unsafe? PROMISE@ICSE 2005: 6:1-6:6 - [c47]Zhihao Chen, Tim Menzies, Dan Port, Barry W. Boehm:
Feature subset selection can improve software cost estimation accuracy. PROMISE@ICSE 2005: 8:1-8:6 - 2004
- [c46]Tim Menzies, Justin S. Di Stefano:
How Good Is Your Blind Spot Sampling Policy? HASE 2004: 129-138 - [c45]Alexander Dekhtyar, Jane Huffman Hayes, Tim Menzies:
Text is Software Too. MSR 2004: 22-26 - [c44]Tim Menzies, Justin S. Di Stefano, Chris Cunanan, Robert (Mike) Chapman:
Mining Repositories to Assist in Project Planning and Resource Allocation. MSR 2004: 75-79 - 2003
- [j22]Tim Menzies, Ying Hu:
Data Mining for Very Busy People. Computer 36(11): 22-29 (2003) - [j21]Tim Menzies:
Guest Editor's Introduction: 21st Century AI--Proud, Not Smug. IEEE Intell. Syst. 18(3): 18-24 (2003) - [j20]Tim Menzies:
Editorial: model-based requirements engineering. Requir. Eng. 8(4): 193-194 (2003) - [j19]Tim Menzies, Justin S. Di Stefano:
More Success and Failure Factors in Software Reuse. IEEE Trans. Software Eng. 29(5): 474-477 (2003) - [c43]Martin S. Feather, Tim Menzies, Judith R. Connelly:
Matching Software Practitioner Needs to Researcher Activities. APSEC 2003: 6-16 - [c42]Yan Liu, Srikanth Gururajan, Bojan Cukic, Tim Menzies, Marcello R. Napolitano:
Validating an Online Adaptive System Using SVDD. ICTAI 2003: 384- - [c41]Tim Menzies, Justin S. Di Stefano, Mike Chapman:
Learning Early Lifecycle IV&V Quality Indicators. IEEE METRICS 2003: 88-97 - [c40]Tim Menzies, Justin S. Di Stefano, Kareem Ammar, Kenneth McGill, Pat Callis, Robert (Mike) Chapman, John Davis:
When Can We Test Less? IEEE METRICS 2003: 98- - [c39]Martin S. Feather, Tim Menzies, Judith R. Connelly:
Relating Practitioner Needs to Research Activities. RE 2003: 352- - [c38]David Owen, Tim Menzies:
Lurch: a Lightweight Alternative to Model Checking. SEKE 2003: 158-165 - [c37]Tim Menzies, Robyn R. Lutz, Ines Carmen Mikulski:
Better Analysis of Defect Data at NASA. SEKE 2003: 607-611 - [c36]Tim Menzies, James D. Kiper, Martin S. Feather:
Improved Software Engineering Decision Support Through Automatic Argument Reduction Tools. SEKE 2003: 655-662 - [c35]David Owen, Tim Menzies, Mats Per Erik Heimdahl, Jimin Gao:
On the Advantages of Approximate vs. Complete Verification: Bigger Models, Faster, Less Memory, Usually Accurate. SEW 2003: 75 - [c34]Dustin Geletko, Tim Menzies:
Model-Based Software Testing via Incremental Treatment Learning. SEW 2003: 82 - 2002
- [j18]Eliza Chiang, Tim Menzies:
Simulations for very early lifecycle quality evaluations. Softw. Process. Improv. Pract. 7(3-4): 141-159 (2002) - [j17]Tim Menzies, Robert F. Cohen, Sam Waugh, Simon Goss:
Applications of Abduction: Testing Very Long Qualitative Simulations. IEEE Trans. Knowl. Data Eng. 14(6): 1362-1375 (2002) - [c33]Tim Menzies, Adrian R. Pearce, Clinton Heinze, Simon Goss:
What Is an Agent and Why Should I Care? FAABS 2002: 1-14 - [c32]Tim Menzies, David Owen, Bojan Cukic:
You Seem Friendly, But Can I Trust You? FAABS 2002: 208-219 - [c31]David Owen, Bojan Cukic, Tim Menzies:
An Alternative to Model Checking: Verification by Random Search of AND-OR Graphs Representing Finite-State Models. HASE 2002: 119-128 - [c30]Yan Liu, Tim Menzies, Bojan Cukic:
Data Sniffing - Monitoring of Machine Learning for Online Adaptive Systems. ICTAI 2002: 16-21 - [c29]Justin S. Di Stefano, Tim Menzies:
Machine Learning for Software Engineering: Case Studies in Software Reuse. ICTAI 2002: 246-251 - [c28]Tim Menzies, David Owen, Bojan Cukic:
Saturation Effects in Testing of Formal Models. ISSRE 2002: 15-26 - [c27]Tim Menzies, David Raffo, Siri-on Setamanit, Ying Hu, Sina Tootoonia:
Model-Based Tests of Truisms. ASE 2002: 183- - [c26]David Owen, Tim Menzies, Bojan Cukic:
What Makes Finite-State Models More (or Less) Testable? ASE 2002: 237-240 - [c25]Martin S. Feather, Tim Menzies:
Converging on the Optimal Attainment of Requirements. RE 2002: 263-272 - [c24]Tim Menzies, Lindsay Mason:
Some prolog macros for rule-based programming: why? how? ACM SIGPLAN Workshop on Rule-Based Programming 2002: 79-92 - 2001
- [c23]Tim Menzies, Harshinder Singh:
How AI Can Help SE; or: Randomized Search Not Considered Harmful. AI 2001: 100-110 - [c22]Tim Menzies, John D. Powell, Michael E. Houle:
Fast Formal Analysis of Requirements via "Topoi Diagrams". ICSE 2001: 391-400 - [c21]Tim Menzies, James D. Kiper:
Better Reasoning About Software Engineering Activities. ASE 2001: 391-394 - 2000
- [j16]Brian Drabble, Laurent Chaudron, Catherine Tessier, Sue Abu-Hakima, Steven Willmott, Jim Austin, Boi Faltings, Eugene C. Freuder, Gerhard Friedrich, Alex Alves Freitas, Ulises Cortés, Miquel Sànchez-Marrè, David W. Aha, Irma Becerra-Fernandez, Héctor Muñoz-Avila, Aditya Ghose, Tim Menzies, Ken Satoh, Mary Elaine Califf, Michael T. Cox, Sandip Sen, Patrick Brézillon, Jean-Charles Pomerol, Roy M. Turner, Elise H. Turner:
Reports on the AAAI 1999 Workshop Program. AI Mag. 21(1): 95-100 (2000) - [j15]Tim Menzies, Bojan Cukic:
Adequacy of Limited Testing for Knowledge Based Systems. Int. J. Artif. Intell. Tools 9(1): 153-172 (2000) - [j14]Tim Menzies, Klaus-Dieter Althoff, Yannis Kalfoglou, Enrico Motta:
Issues with Meta-Knowledge. Int. J. Softw. Eng. Knowl. Eng. 10(4): 549-555 (2000) - [j13]Yannis Kalfoglou, Tim Menzies, Klaus-Dieter Althoff, Enrico Motta:
Meta-knowledge in systems design: panacea ... or undelivered promise? Knowl. Eng. Rev. 15(4): 381-404 (2000) - [j12]Tim Menzies, Bojan Cukic:
When to Test Less. IEEE Softw. 17(5): 107-112 (2000) - [c20]Tim Menzies, Bojan Cukic, Harshinder Singh:
Agents Talking Faster. FAABS 2000: 194-208 - [c19]Tim Menzies:
WISE3: the Third International Workshop on Intelligent Software Engineering (workshop session). ICSE 2000: 812-813 - [c18]Tim Menzies, Bojan Cukic, Harshinder Singh, John D. Powell:
Testing Nondeterminate Systems. ISSRE 2000: 222-233 - [c17]Tim Menzies:
The Complexity of TRMCS-like Spiral Specification. IWSSD 2000: 183-190 - [c16]Tim Menzies, Erik Sinsel:
Practical Large Scale What-If Queries: Case Studies with Software Risk Assessment. ASE 2000: 165-
1990 – 1999
- 1999
- [j11]Tim Menzies:
Desert Island Column. Autom. Softw. Eng. 6(3): 315-320 (1999) - [j10]Tim Menzies, Frank van Harmelen:
Editorial: Evaluating knowledge engineering techniques. Int. J. Hum. Comput. Stud. 51(4): 715-727 (1999) - [j9]Tim Menzies:
Critical success metrics: evaluation at the business level. Int. J. Hum. Comput. Stud. 51(4): 783-799 (1999) - [j8]Tim Menzies:
Knowledge maintenance: the state of the art. Knowl. Eng. Rev. 14(1): 1-46 (1999) - [j7]Tim Menzies:
Cost benefits of ontologies. Intell. 10(3): 26-32 (1999) - [c15]Tim Menzies, Bojan Cukic:
On the Sufficiency of Limited Testing for Knowledge Based Systems. ICTAI 1999: 431-440 - [c14]Tim Menzies, Steve M. Easterbrook, Bashar Nuseibeh, Sam Waugh:
An Empirical Investigation of Multiple Viewpoint Reasoning in Requirements Engineering. RE 1999: 100- - 1998
- [j6]Tim Menzies, William J. Clancey:
Editorial: the challenge of situated cognition for symbolic knowledge-based systems. Int. J. Hum. Comput. Stud. 49(6): 767-769 (1998) - [j5]Tim Menzies:
Towards situated knowledge acquisition. Int. J. Hum. Comput. Stud. 49(6): 867-893 (1998) - [c13]Tim Menzies, Sam Waugh:
Lower Bounds on the Size of Test Data Sets. Australian Joint Conference on Artificial Intelligence 1998: 227-237 - [c12]Sam Waugh, Brian Hanlon, Tim Menzies:
The Temporal QCM Modelling Language. Australian Joint Conference on Artificial Intelligence 1998: 262-272 - [c11]Tim Menzies, Sam Waugh:
Lower Bounds on the Size of Test Data Sets. EUROVAV 1998 - [c10]Tim Menzies, Sam Waugh:
On the Practicality of Viewpoint-Based Requirements Engineering. PRICAI 1998: 110-121 - 1997
- [j4]Tim Menzies, Paul Compton:
Applications of abduction: hypothesis testing of neuroendocrinological qualitative compartmental models. Artif. Intell. Medicine 10(2): 145-175 (1997) - [j3]Tim Menzies:
Object-Oriented Patterns: Lessons from Expert Systems. Softw. Pract. Exp. 27(12): 1457-1478 (1997) - [c9]Sam Waugh, Tim Menzies, Simon Goss:
Evaluating a Qualitative Reasoner. Australian Joint Conference on Artificial Intelligence 1997: 505-514 - [c8]Tim Menzies, Robert F. Cohen:
A Graph Theoretic Optimisation of Temporal Abductive Validation. EUROVAV 1997: 55-68 - 1996
- [j2]Tim Menzies:
Applications of abduction: knowledge-level modelling. Int. J. Hum. Comput. Stud. 45(3): 305-335 (1996) - [c7]Tim Menzies:
On the Practicality of Abductive Validation. ECAI 1996: 23-27 - [c6]Tim Menzies:
Visual Programming, Knowledge Engineering, and Software Engineering. SEKE 1996: 506-513 - 1993
- [c5]Philip Haynes, Tim Menzies:
"C++ is Better Than Smalltalk"?? TOOLS (12/9) 1993: 75-82 - [c4]Tim Menzies, Richard Spurrett:
How to Edit "It"; or: A "Black-box" Constraint-Based Framework for User-Interaction with Arbitrary Structures. TOOLS (12/9) 1993: 213-224 - [c3]Tim Menzies, Julian M. Edwards, Kekwee Ng:
The Mysterious Case of the Missing Reusable Class Libraries. TOOLS (12/9) 1993: 421-427 - 1992
- [c2]Tim Menzies:
Is-a Object Part-of Knowledge Representation (Part 2). TOOLS (6) 1992: 213-223
1980 – 1989
- 1989
- [j1]Tim Menzies:
An Investigation of AI and Expert Systems Literature: 1980-1984. AI Mag. 10(2): 53-61 (1989) - 1988
- [c1]Tim Menzies, M. Dean, J. L. Black, J. F. Fleming:
Combining Heuristics and Simulation Models: An Expert System for the Optimal Management of Pigs. Australian Joint Conference on Artificial Intelligence 1988: 48-61
Coauthor Index
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