Marouane Kessentini

Early prediction of quality of service using interface-level metrics, code-level metrics, and antipatterns.
https://www.sciencedirect.com/science/article/abs/pii/S0950584920300653

On the value of quality attributes for refactoring ATL model transformations: A multi-objective approach.
https://www.sciencedirect.com/science/article/abs/pii/S0950584919302617

Web service design defects detection: A bi-level multi-objective approach.
https://www.sciencedirect.com/science/article/abs/pii/S0950584919302733?via%3Dihub

Assessing the quality of mobile graphical user interfaces using multi-objective optimization.
https://link.springer.com/article/10.1007%2Fs00500-019-04391-8

On the Impact of Refactoring on the Relationship between Quality Attributes and Design Metrics
https://ieeexplore.ieee.org/document/8870177

Intelligent Software Refactoring Bot
https://ieeexplore.ieee.org/document/8952287

Interactive Refactoring Documentation Bot
https://ieeexplore.ieee.org/document/8930873

Less is More: From Multi-objective to Mono-objective Refactoring via Developer's Knowledge Extraction
https://ieeexplore.ieee.org/document/8930882

Simultaneous Refactoring and Regression Testing
https://ieeexplore.ieee.org/document/8930845

Refactoring Support for Variability-intensive Systems
https://www.taylorfrancis.com/chapters/edit/10.1201/9780429022067-15/refactoring-support-variability-intensive-systems-vahid-alizadeh-marouane-kessentini-bruce-maxim

Do Design Metrics Capture Developers Perception of Quality? An Empirical Study on Self-Affirmed Refactoring
https://arxiv.org/abs/1907.04797

Understanding the correlation between code smells and software bugs.
https://deepblue.lib.umich.edu/bitstream/handle/2027.42/147342/CodeSmellsBugs.pdf

Improving web service interfaces modularity using multi-objective optimization.
https://link.springer.com/article/10.1007/s10515-019-00256-4

Refactoring Web Services Interface Using Many-Objective Search.
https://deepblue.lib.umich.edu/bitstream/handle/2027.42/153330/EMSE-wang-2016.pdf?sequence=1

Interactive and dynamic search based approach to software refactoring recommendations.
https://patentimages.storage.googleapis.com/92/15/2f/f0071b4add1f71/US20190317760A1.pdf

Interactive Refactoring via Clustering-Based Multi-objective Search.
https://deepblue.lib.umich.edu/bitstream/handle/2027.42/153328/ASE2018_Clustering_The_Pareto_Optimal_Solutions__Copy_DeepBlue.pdf?sequence=1

A Tutorial on Software Engineering Intelligence: Case Studies on Model-Driven Engineering.
https://deepblue.lib.umich.edu/bitstream/handle/2027.42/153783/MODELS_Tutorial__SEI___Copy_.pdf?sequence=1

Interactive Software Refactoring Bot.
https://deepblue.lib.umich.edu/bitstream/handle/2027.42/153326/ASE2019_RefactoringBot__Copy_deepblue.pdf?sequence=1

A Refactoring Documentation Bot.
https://deepblue.lib.umich.edu/bitstream/handle/2027.42/153325/TSE_DocumentationBot__Copy_deep_blue.pdf?sequence=1

Code Reviewer Recommendations as a Multi-Objective Problem: Balancing Expertise, Availability and Collaborations.
https://link.springer.com/article/10.1007/s10515-020-00275-6

Refactorings Recommendation via Commit Message Analysis.
https://www.sciencedirect.com/science/article/abs/pii/S0950584920300914

Multi-criteria test cases selection for model transformations.
https://link.springer.com/article/10.1007/s10515-020-00271-w

How Does Refactoring Impact Security When Improving Quality? A Security-Aware Refactoring Approach.
https://www.computer.org/csdl/journal/ts/2022/03/09130035/1l59oymq44E

30 years of software refactoring research: A systematic literature review.
https://www.researchgate.net/publication/342734042_30_Years_of_Software_Refactoring_ResearchA_Systematic_Literature_Review

Interactive Multi-Objective Refactoring via Decision and Objective Space Exploration
https://deepblue.lib.umich.edu/bitstream/handle/2027.42/162566/ICSE2020_Decision_Objective_Spaces_copy%20%282%29.pdf?sequence=1

Enabling decision and objective space exploration for interactive multi-objective refactoring.
https://ieeexplore.ieee.org/abstract/document/9200705

Qscored: An open platform for code quality ranking and visualization
https://ieeexplore.ieee.org/abstract/document/9240671

Understanding and Characterizing Changes in Bugs Priority: The Practitioners’ Perceptive
https://deepblue.lib.umich.edu/bitstream/handle/2027.42/163322/Empirical_Study_Bug_Priority_Final%20%2834%29.pdf?sequence=1

Recommending refactorings via commit message analysis.
https://www.sciencedirect.com/science/article/abs/pii/S0950584920300914

How we refactor and how we document it? On the use of supervised machine learning algorithms to classify refactoring documentation.
https://www.sciencedirect.com/science/article/abs/pii/S095741742030912X

Applying Many-objective Algorithms to the Variability Test of Software Product Lines
https://dl.acm.org/doi/abs/10.1145/3425174.3425211

Considering Dependencies Between Bug Reports to Improve Bugs Triage.
https://link.springer.com/article/10.1007/s10515-020-00279-2

Method-level bug localization using hybrid multi-objective search.
https://www.sciencedirect.com/science/article/abs/pii/S0950584920302196

Nautilus: An Interactive Plug-and-Play Search-Based Software Engineering Framework.
https://ieeexplore.ieee.org/document/9264666

Multi-objective code reviewer recommendations: balancing expertise, availability and collaborations
https://link.springer.com/article/10.1007/s10515-020-00275-6

Knowledge incorporation in requirements traceability recovery. Information Science and Applications
https://link.springer.com/chapter/10.1007/978-981-33-6385-4_24

Refactoring Practices in the Context of Modern Code Review: An Industrial Case Study at Xerox
https://ieeexplore.ieee.org/document/9401999

On the impact of aesthetic defects on the maintainability of mobile graphical user interfaces: An empirical study
https://link.springer.com/article/10.1007/s10796-020-10100-w

Considering dependencies between bug reports to improve bugs triage
https://link.springer.com/article/10.1007/s10515-020-00279-2

Interactive Decision and Objective Space Exploration for Search Based Refactoring
https://deepblue.lib.umich.edu/bitstream/handle/2027.42/170142/ICSE2020_Decision_Objective_Spaces__Copy_.pdf?sequence=1

Qscored: A large dataset of code smells and quality metrics
https://ieeexplore.ieee.org/abstract/document/9463095

Refactorings and Technical Debt in Docker Projects: An Empirical Study
https://deepblue.lib.umich.edu/bitstream/handle/2027.42/170138/ASE2021_DockerRefactoring__Copy_.pdf

X-SBR: On the use of the history of refactorings for explainable search-based refactoring and intelligent change operators
https://ieeexplore.ieee.org/abstract/document/9514445

Implementing Search-Based Software Engineering Approaches with Nautilus
https://dl.acm.org/doi/abs/10.1145/3474624.3476010

NSGA-II as feature selection technique and AdaBoost classifier for COVID-19 prediction using patient’s symptoms
https://link.springer.com/article/10.1007/s11071-021-06504-1

MDE Intelligence 2021: 3rd Workshop on Artificial Intelligence and Model-Driven Engineering.
https://ieeexplore.ieee.org/abstract/document/9643764

Prioritizing refactorings for security-critical code
https://link.springer.com/article/10.1007/s10515-021-00281-2

A Systematic Literature Review on Software Maintenance for Cyber-Physical Systems
https://ieeexplore.ieee.org/abstract/document/9606906

Intelligent change operators for multi-objective refactoring
https://ieeexplore.ieee.org/abstract/document/9678519

What Refactoring Topics Do Developers Discuss? A Large Scale Empirical Study Using Stack Overflow
https://ieeexplore.ieee.org/abstract/document/9667359

Requirements traceability recovery for the purpose of software reuse: an interactive genetic algorithm approach
https://link.springer.com/article/10.1007/s11334-021-00418-2

Industry's cry for tools that support large-scale refactoring
https://dl.acm.org/doi/abs/10.1145/3510457.3513074

Generation of refactoring algorithms by grammatical evolution
https://link.springer.com/article/10.1007/s10664-022-10151-4

Industry experiences with large-scale refactoring
https://dl.acm.org/doi/abs/10.1145/3540250.3558954

Variability testing of software product line: A preference-based dimensionality reduction approach
https://www.sciencedirect.com/science/article/abs/pii/S0950584922001501

An empirical study on ML DevOps adoption trends, efforts, and benefits analysis
https://www.sciencedirect.com/science/article/abs/pii/S0950584922001537

EASE: An effort-aware extension of unsupervised key class identification approaches
https://dl.acm.org/doi/abs/10.1145/3635714

Dependent or Not: Detecting and Understanding Collections of Refactorings
https://ieeexplore.ieee.org/abstract/document/10048003

Dynamic Software Containers Workload Balancing Via Many-Objective Search
https://ieeexplore.ieee.org/abstract/document/10048583

The state of accessibility in blackboard: Survey and user reviews case study
https://dl.acm.org/doi/abs/10.1145/3587281.3587291

Vulnerability Analysis of Docker Hub Official Images and Verified Images
https://ieeexplore.ieee.org/abstract/document/10254755

Leveraging Artificial Intelligence for Model-based Software Analysis and Design
https://link.springer.com/chapter/10.1007/978-981-19-9948-2_4

Examining deep learning’s capability to spot code smells: a systematic literature review
https://link.springer.com/article/10.1007/s10586-023-04144-1

A Systematic Literature Review on Maintenance of Software Containers
https://dl.acm.org/doi/abs/10.1145/3645092

Public Transport Travel Time Prediction using Sequential Forward Floating Selection Algorithm and Stacked Autoencoder.
https://www.taylorfrancis.com/chapters/edit/10.1201/9781032629537-13/public-transport-travel-time-prediction-using-sequential-forward-floating-selection-algorithm-stacked-autoencoder-makram-soui-ines-gasmi-nesrine-mansouri-imen-ben-rjeb-marouane-kessentin

International Workshop on Refactoring IWoR CHarter
https://deepblue.lib.umich.edu/bitstream/handle/2027.42/155873/Charter_for_the_International_Workshop_on_Refactoring__IWoR_.pdf?sequence=1

Integrated strategy of Vehicle Routing and Maintenance
https://www.sciencedirect.com/science/article/abs/pii/S0951832017303174