Timothy James Menzies

(Re)Use of Research Results (Is Rampant)

COMMUNICATIONS OF THE ACM, 66(2), 75–81.

An expert system for redesigning software for cloud applications

EXPERT SYSTEMS WITH APPLICATIONS, 219.

VEER: enhancing the interpretability of model-based optimizations

EMPIRICAL SOFTWARE ENGINEERING, 28(3).

Artificial Intelligence and Software Engineering: Are We Ready?

COMPUTER, 55(3), 24–28.

Assessing expert system-assisted literature reviews with a case study

EXPERT SYSTEMS WITH APPLICATIONS, 200.

Better Data Labelling With EMBLEM (and how that Impacts Defect Prediction)

IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, 48(1), 278–294.

Dazzle: Using Optimized Generative Adversarial Networks to Address Security Data Class Imbalance Issue

2022 MINING SOFTWARE REPOSITORIES CONFERENCE (MSR 2022), pp. 144–155.

Do I really need all this work to find vulnerabilities? An empirical case study comparing vulnerability detection techniques on a Java application

EMPIRICAL SOFTWARE ENGINEERING, 27(6).

How to Improve Deep Learning for Software Analytics (a case study with code smell detection)

2022 MINING SOFTWARE REPOSITORIES CONFERENCE (MSR 2022), pp. 156–166.

Identifying Self-Admitted Technical Debts With Jitterbug: A Two-Step Approach

IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, 48(5), 1676–1691.

Methods for Stabilizing Models Across Large Samples of Projects (with case studies on Predicting Defect and Project Health)

2022 MINING SOFTWARE REPOSITORIES CONFERENCE (MSR 2022), pp. 566–578.

Omni: automated ensemble with unexpected models against adversarial evasion attack

EMPIRICAL SOFTWARE ENGINEERING, 27(1).

Predicting health indicators for open source projects (using hyperparameter optimization)

EMPIRICAL SOFTWARE ENGINEERING, 27(6).

Revisiting process versus product metrics: a large scale analysis

EMPIRICAL SOFTWARE ENGINEERING, 27(3).

Sequential Model Optimization for Software Effort Estimation

IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, 48(6), 1994–2009.

The Secret to Better AI and Better Software (Is Requirements Engineering)

Bencomo, N., Guo, J. L. C., Harrison, R., Heyn, H.-M., & Menzies, T. (2022, January). IEEE SOFTWARE, Vol. 39, pp. 105–110.

Assessing practitioner beliefs about software engineering

EMPIRICAL SOFTWARE ENGINEERING, 26(4).

Bias in Machine Learning Software: Why? How? What to Do?

PROCEEDINGS OF THE 29TH ACM JOINT MEETING ON EUROPEAN SOFTWARE ENGINEERING CONFERENCE AND SYMPOSIUM ON THE FOUNDATIONS OF SOFTWARE ENGINEERING (ESEC/FSE '21), pp. 429–440.

Characterizing Crowds to Better Optimize Worker Recommendation in Crowdsourced Testing

IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, 47(6), 1259–1276.

Documenting Evidence of a Replication of 'Analyze This! 145 Questions for Data Scientists in Software Engineering'

PROCEEDINGS OF THE 29TH ACM JOINT MEETING ON EUROPEAN SOFTWARE ENGINEERING CONFERENCE AND SYMPOSIUM ON THE FOUNDATIONS OF SOFTWARE ENGINEERING (ESEC/FSE '21), pp. 1602–1602.

Documenting Evidence of a Replication of 'Populating a Release History Database from Version Control and Bug Tracking Systems'

PROCEEDINGS OF THE 29TH ACM JOINT MEETING ON EUROPEAN SOFTWARE ENGINEERING CONFERENCE AND SYMPOSIUM ON THE FOUNDATIONS OF SOFTWARE ENGINEERING (ESEC/FSE '21), pp. 1601–1601.

Documenting Evidence of a Reproduction of Is There A "Golden" Feature Set for Static Warning Identification? - An Experimental Evaluation'

PROCEEDINGS OF THE 29TH ACM JOINT MEETING ON EUROPEAN SOFTWARE ENGINEERING CONFERENCE AND SYMPOSIUM ON THE FOUNDATIONS OF SOFTWARE ENGINEERING (ESEC/FSE '21), pp. 1603–1603.

Documenting Evidence of a Reuse of "'Why Should I Trust You?": Explaining the Predictions of Any Classifier'

PROCEEDINGS OF THE 29TH ACM JOINT MEETING ON EUROPEAN SOFTWARE ENGINEERING CONFERENCE AND SYMPOSIUM ON THE FOUNDATIONS OF SOFTWARE ENGINEERING (ESEC/FSE '21), pp. 1600–1600.

Documenting Evidence of a Reuse of 'A Systematic Literature Review of Techniques and Metrics to Reduce the Cost of Mutation Testing'

PROCEEDINGS OF THE 29TH ACM JOINT MEETING ON EUROPEAN SOFTWARE ENGINEERING CONFERENCE AND SYMPOSIUM ON THE FOUNDATIONS OF SOFTWARE ENGINEERING (ESEC/FSE '21), pp. 1597–1597.

Documenting Evidence of a Reuse of 'A Systematic Study of the Class Imbalance Problem in Convolutional Neural Networks'

PROCEEDINGS OF THE 29TH ACM JOINT MEETING ON EUROPEAN SOFTWARE ENGINEERING CONFERENCE AND SYMPOSIUM ON THE FOUNDATIONS OF SOFTWARE ENGINEERING (ESEC/FSE '21), pp. 1595–1595.

Documenting Evidence of a Reuse of 'On the Number of Linear Regions of Deep Neural Networks'

PROCEEDINGS OF THE 29TH ACM JOINT MEETING ON EUROPEAN SOFTWARE ENGINEERING CONFERENCE AND SYMPOSIUM ON THE FOUNDATIONS OF SOFTWARE ENGINEERING (ESEC/FSE '21), pp. 1596–1596.

Documenting Evidence of a Reuse of 'RefactoringMiner 2.0'

PROCEEDINGS OF THE 29TH ACM JOINT MEETING ON EUROPEAN SOFTWARE ENGINEERING CONFERENCE AND SYMPOSIUM ON THE FOUNDATIONS OF SOFTWARE ENGINEERING (ESEC/FSE '21), pp. 1598–1598.

Documenting Evidence of a Reuse of 'What is a Feature? A Qualitative Study of Features in Industrial Software Product Lines'

PROCEEDINGS OF THE 29TH ACM JOINT MEETING ON EUROPEAN SOFTWARE ENGINEERING CONFERENCE AND SYMPOSIUM ON THE FOUNDATIONS OF SOFTWARE ENGINEERING (ESEC/FSE '21), pp. 1599–1599.

Early Life Cycle Software Defect Prediction. Why? How?

2021 IEEE/ACM 43RD INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING (ICSE 2021), pp. 448–459.

FRUGAL: Unlocking Semi-Supervised Learning for Software Analytics

2021 36TH IEEE/ACM INTERNATIONAL CONFERENCE ON AUTOMATED SOFTWARE ENGINEERING ASE 2021, pp. 394–406.

How to Better Distinguish Security Bug Reports (Using Dual Hyperparameter Optimization)

EMPIRICAL SOFTWARE ENGINEERING, 26(3).

Improving Vulnerability Inspection Efficiency Using Active Learning

IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, 47(11), 2401–2420.

Learning to recognize actionable static code warnings (is intrinsically easy)

EMPIRICAL SOFTWARE ENGINEERING, 26(3).

Mining Workflows for Anomalous Data Transfers

2021 IEEE/ACM 18TH INTERNATIONAL CONFERENCE ON MINING SOFTWARE REPOSITORIES (MSR 2021), pp. 1–12.

On the Value of Oversampling for Deep Learning in Software Defect Prediction

IEEE Transactions on Software Engineering, 48(8), 1–1.

Shockingly Simple: "Keys" for Better AI for SE

IEEE SOFTWARE, Vol. 38, pp. 114–118.

Simpler Hyperparameter Optimization for Software Analytics: Why, How, When

IEEE Transactions on Software Engineering, 48(8), 1–1.

Structuring a Comprehensive Software Security Course Around the OWASP Application Security Verification Standard

2021 IEEE/ACM 43RD INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING: JOINT TRACK ON SOFTWARE ENGINEERING EDUCATION AND TRAINING (ICSE-JSEET 2021), pp. 95–104.

Understanding static code warnings: An incremental AI approach

EXPERT SYSTEMS WITH APPLICATIONS, 167.

Whence to Learn? Transferring Knowledge in Configurable Systems Using BEETLE

IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, 47(12), 2956–2972.

Assessing Practitioner Beliefs about Software Defect Prediction

2020 IEEE/ACM 42ND INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING: SOFTWARE ENGINEERING IN PRACTICE (ICSE-SEIP), pp. 182–190.

Better software analytics via "DUO": Data mining algorithms using/used-by optimizers

EMPIRICAL SOFTWARE ENGINEERING, 25(3), 2099–2136.

Expert Perspectives on AI

IEEE SOFTWARE, Vol. 37, pp. 87–94.

Learning actionable analytics from multiple software projects

EMPIRICAL SOFTWARE ENGINEERING, 25(5), 3468–3500.

Making Fair ML Software using Trustworthy Explanation

2020 35TH IEEE/ACM INTERNATIONAL CONFERENCE ON AUTOMATED SOFTWARE ENGINEERING (ASE 2020), pp. 1229–1233.

The AI Effect: Working at the Intersection of AI and SE

IEEE SOFTWARE, Vol. 37, pp. 26–35.

The Five Laws of SE for AI

IEEE SOFTWARE, Vol. 37, pp. 81–85.

What disconnects Practitioner Belief and Empirical Evidence ?

2020 ACM/IEEE 42ND INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING: COMPANION PROCEEDINGS (ICSE-COMPANION 2020), pp. 286–287.

iSENSE2.0: Improving Completion-aware Crowdtesting Management with Duplicate Tagger and Sanity Checker

ACM TRANSACTIONS ON SOFTWARE ENGINEERING AND METHODOLOGY, 29(4).

"Bad smells" in software analytics papers

INFORMATION AND SOFTWARE TECHNOLOGY, 112, 35–47.

"Sampling" as a Baseline Optimizer for Search-Based Software Engineering

IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, 45(6), 597–614.

A Deep Learning Model for Estimating Story Points

IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, 45(7), 637–656.

Bellwethers: A Baseline Method for Transfer Learning

IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, 45(11), 1081–1105.

FAST(2): An intelligent assistant for finding relevant papers

EXPERT SYSTEMS WITH APPLICATIONS, 120, 57–71.

How to "DODGE" Complex Software Analytics

IEEE Transactions on Software Engineering, 47(10), 1–1.

Images don't lie: Duplicate crowdtesting reports detection with screenshot information

INFORMATION AND SOFTWARE TECHNOLOGY, 110, 139–155.

Predicting Breakdowns in Cloud Services (with SPIKE)

ESEC/FSE'2019: PROCEEDINGS OF THE 2019 27TH ACM JOINT MEETING ON EUROPEAN SOFTWARE ENGINEERING CONFERENCE AND SYMPOSIUM ON THE FOUNDATIONS OF SOFTWARE ENGINEERING, pp. 916–924.

TERMINATOR: Better Automated UI Test Case Prioritization

ESEC/FSE'2019: PROCEEDINGS OF THE 2019 27TH ACM JOINT MEETING ON EUROPEAN SOFTWARE ENGINEERING CONFERENCE AND SYMPOSIUM ON THE FOUNDATIONS OF SOFTWARE ENGINEERING, pp. 883–894.

Take Control (On the Unreasonable Effectiveness of Software Analytics)

2019 IEEE/ACM 41ST INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING: SOFTWARE ENGINEERING IN PRACTICE (ICSE-SEIP 2019), pp. 265–266.

iSENSE: Completion-Aware Crowdtesting Management

2019 IEEE/ACM 41ST INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING (ICSE 2019), pp. 912–923.

Actionable Analytics for Software Engineering INTRODUCTION

IEEE SOFTWARE, Vol. 35, pp. 51–53.

Applications of Psychological Science for Actionable Analytics

ESEC/FSE'18: PROCEEDINGS OF THE 2018 26TH ACM JOINT MEETING ON EUROPEAN SOFTWARE ENGINEERING CONFERENCE AND SYMPOSIUM ON THE FOUNDATIONS OF SOFTWARE ENGINEERING, pp. 456–467.

Beyond evolutionary algorithms for search-based software engineering

INFORMATION AND SOFTWARE TECHNOLOGY, 95, 281–294.

Data-Driven Search-based Software Engineering

2018 IEEE/ACM 15TH INTERNATIONAL CONFERENCE ON MINING SOFTWARE REPOSITORIES (MSR), pp. 341–352.

Faster discovery of faster system configurations with spectral learning

AUTOMATED SOFTWARE ENGINEERING, 25(2), 247–277.

Finding better active learners for faster literature reviews

EMPIRICAL SOFTWARE ENGINEERING, 23(6), 3161–3186.

Guest Editorial for the Special Section from the 9th International Symposium on Search Based Software Engineering

Petke, J., & Menzies, T. (2018, December). INFORMATION AND SOFTWARE TECHNOLOGY, Vol. 104, pp. 194–194.

Heterogeneous Defect Prediction

IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, 44(9), 874–896.

Is "Better Data" Better Than "Better Data Miners"? On the Benefits of Tuning SMOTE for Defect Prediction

PROCEEDINGS 2018 IEEE/ACM 40TH INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING (ICSE), pp. 1050–1061.

Micky: A Cheaper Alternative for Selecting Cloud Instances

PROCEEDINGS 2018 IEEE 11TH INTERNATIONAL CONFERENCE ON CLOUD COMPUTING (CLOUD), pp. 409–416.

RIOT: a Stochastic-based Method for Workflow Scheduling in the Cloud

PROCEEDINGS 2018 IEEE 11TH INTERNATIONAL CONFERENCE ON CLOUD COMPUTING (CLOUD), pp. 318–325.

The Unreasonable Effectiveness of Software Analytics

IEEE SOFTWARE, 35(2), 96–98.

Total Recall, Language Processing, and Software Engineering

PROCEEDINGS OF THE 4TH ACM SIGSOFT INTERNATIONAL WORKSHOP ON NLP FOR SOFTWARE ENGINEERING (NL4SE '18), pp. 10–13.

VOICE OF EVIDENCE From Voice of Evidence to Redirections

IEEE SOFTWARE, Vol. 35, pp. 11–13.

What is wrong with topic modeling? And how to fix it using search-based software engineering

INFORMATION AND SOFTWARE TECHNOLOGY, 98, 74–88.

A guest editorial: special issue on search based software engineering and data mining

Kessentini, M., & Menzies, T. (2017, September). AUTOMATED SOFTWARE ENGINEERING, Vol. 24, pp. 573–574.

Are delayed issues harder to resolve? Revisiting cost-to-fix of defects throughout the lifecycle

EMPIRICAL SOFTWARE ENGINEERING, 22(4), 1903–1935.

Less is more: Minimizing code reorganization using XTREE

INFORMATION AND SOFTWARE TECHNOLOGY, 88, 53–66.

Negative results for software effort estimation

EMPIRICAL SOFTWARE ENGINEERING, 22(5), 2658–2683.

TMAP: Discovering relevant API methods through text mining of API documentation

Journal of Software: Evolution and Process, 29(12), e1845.

The NASA analogy software cost model: A web-based cost analysis tool

2017 ieee aerospace conference.

Using Bad Learners to Find Good Configurations

ESEC/FSE 2017: PROCEEDINGS OF THE 2017 11TH JOINT MEETING ON FOUNDATIONS OF SOFTWARE ENGINEERING, pp. 257–267.

"How not to Do it": Anti-patterns for Data Science in Software Engineering

2016 IEEE/ACM 38TH INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING COMPANION (ICSE-C), pp. 887–887.

An (Accidental) Exploration of Alternatives to Evolutionary Algorithms for SBSE

SEARCH BASED SOFTWARE ENGINEERING, SSBSE 2016, Vol. 9962, pp. 96–111.

Correlation is not causation (or, when not to scream "Eureka!")

Perspectives on Data Science for Software Engineering, 327–330.

Improving and expanding NASA software cost estimation methods

2016 ieee aerospace conference.

Learning Mitigations for Pilot Issues When Landing Aircraft (via Multiobjective Optimization and Multiagent Simulations)

IEEE TRANSACTIONS ON HUMAN-MACHINE SYSTEMS, 46(2), 221–230.

Perspectives on data science for software engineering

Perspectives on Data Science for Software Engineering, 3–6.

Seven principles of inductive software engineering: What we do is different

Perspectives on Data Science for Software Engineering, 13–17.

Too Much Automation? The Bellwether Effect and Its Implications for Transfer Learning

2016 31ST IEEE/ACM INTERNATIONAL CONFERENCE ON AUTOMATED SOFTWARE ENGINEERING (ASE), pp. 122–131.

Topic Modeling of NASA Space System Problem Reports

13TH WORKING CONFERENCE ON MINING SOFTWARE REPOSITORIES (MSR 2016), pp. 303–314.

Tuning for software analytics: Is it really necessary?

Information and Software Technology, 76, 135–146.

1st International Workshop on Big Data Software Engineering (BIGDSE 2015)

2015 IEEE/ACM 37th IEEE International Conference on Software Engineering, Vol 2, pp. 965–966.

Actionable = Cluster plus Contrast?

2015 30TH IEEE/ACM INTERNATIONAL CONFERENCE ON AUTOMATED SOFTWARE ENGINEERING WORKSHOP (ASEW), pp. 14–17.

Cross-Project Data for Software Engineering

Menzies, T. (2015, December). COMPUTER, Vol. 48, pp. 6–6.

Data Mining Methods and Cost Estimation Models Why is it so hard to infuse new ideas?

2015 30TH IEEE/ACM INTERNATIONAL CONFERENCE ON AUTOMATED SOFTWARE ENGINEERING WORKSHOP (ASEW), pp. 5–9.

GALE: Geometric Active Learning for Search-Based Software Engineering

IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, 41(10), 1001–1018.

Guest editorial: special issue on realizing AI synergies in software engineering

Harrison, R., & Menzies, T. (2015, March). AUTOMATED SOFTWARE ENGINEERING, Vol. 22, pp. 1–2.

Guest editorial: special issue on realizing AI synergies in software engineering (part 2)

Automated Software Engineering, 22(2), 143–144.

Guest editorial: special multi-issue on selected topics in Automated Software Engineering

Menzies, T., & Pasareanu, C. (2015, September). AUTOMATED SOFTWARE ENGINEERING, Vol. 22, pp. 289–290.

Guest editorial: special multi-issue on selected topics in automated software engineering

Automated Software Engineering, 22(4), 437–438.

LACE2: Better privacy-preserving data sharing for cross project defect prediction

2015 IEEE/ACM 37th IEEE International Conference on Software Engineering, Vol 1, 801–811.

Reduced-Item Food Audits Based on the Nutrition Environment Measures Surveys

American Journal of Preventive Medicine, 49(4), e23–e33.

The Art and Science of Analyzing Software Data; Quantitative Methods

2015 IEEE/ACM 37th IEEE International Conference on Software Engineering, Vol 2, pp. 959–960.

Transfer learning in effort estimation

Empirical Software Engineering, 20(3), 813–843.

Choose to Change: The West Virginia Early Childhood Obesity Prevention Project

Journal of Nutrition Education and Behavior, 46(4), S197.

Special issue on realizing artificial intelligence synergies in software engineering

Software Quality Journal, 22(1), 49–50.

Choose to Change: The West Virginia Early Childhood Obesity Prevention Project

Journal of Nutrition Education and Behavior, 45(4), S92.

Guest editorial for the Special Section on BEST PAPERS from the 2011 conference on Predictive Models in Software Engineering (PROMISE)

Information and Software Technology, 55(8), 1477–1478.

Predictive models in software engineering

Empirical Software Engineering, 18(3), 433–434.

Software effort models should be assessed via leave-one-out validation

Journal of Systems and Software, 86(7), 1879–1890.

Crowd-Sourced Knowledge Bases

In Knowledge Management and Acquisition for Intelligent Systems (pp. 258–271).

Finding conclusion stability for selecting the best effort predictor in software effort estimation

Automated Software Engineering, 20(4), 543–567.

Special issue on repeatable results in software engineering prediction

Empirical Software Engineering, 17(1-2), 1–17.

Guest editorial: learning to organize testing

Automated Software Engineering, 19(2), 137–140.

Kernel methods for software effort estimation

Empirical Software Engineering, 18(1), 1–24.

Learning patterns of university student retention

Expert Systems with Applications, 38(12), 14984–14996.

A second look at Faster, Better, Cheaper

Innovations in Systems and Software Engineering, 6(4), 319–335.

Automatically finding the control variables for complex system behavior

Automated Software Engineering, 17(4), 439–468.

Defect prediction from static code features: current results, limitations, new approaches

Automated Software Engineering, 17(4), 375–407.

Practical considerations in deploying statistical methods for defect prediction: A case study within the Turkish telecommunications industry

Information and Software Technology, 52(11), 1242–1257.

Regularities in Learning Defect Predictors

In Product-Focused Software Process Improvement (pp. 116–130).

Sharing experiments using open-source software

Software: Practice and Experience, 41(3), 283–305.

Stable rankings for different effort models

Automated Software Engineering, 17(4), 409–437.

Accurate estimates without local data?

Software Process: Improvement and Practice, 14(4), 213–225.

Finding robust solutions in requirements models

Automated Software Engineering, 17(1), 87–116.

On the Relative Merits of Software Reuse

In Trustworthy Software Development Processes (pp. 186–197).

On the relative value of cross-company and within-company data for defect prediction

Empirical Software Engineering, 14(5), 540–578.

Accurate Estimates without Calibration?

In Making Globally Distributed Software Development a Success Story (pp. 210–221).

Editorial, special issue, repeatable experiments in software engineering

Empirical Software Engineering, 13(5), 469–471.

Learning better IV&V practices

Innovations in Systems and Software Engineering, 4(2), 169–183.

Special issue on information retrieval for program comprehension

Empirical Software Engineering, 14(1), 1–4.

Just enough learning (of association rules): the TAR2 “Treatment” learner

Artificial Intelligence Review, 25(3), 211–229.

Mining repositories to assist in project planning and resource allocation

"International Workshop on Mining Software Repositories (MSR 2004)" W17S Workshop - 26th International Conference on Software Engineering. Presented at the "International Workshop on Mining Software Repositories (MSR 2004)" W17S Workshop - 26th International Conference on Software Engineering.