Marco Zanoni

Orcid: 0000-0002-6590-0195

According to our database1, Marco Zanoni authored at least 43 papers between 2008 and 2019.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

Legend:

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Bibliography

2019
Toward a Smell-Aware Bug Prediction Model.
IEEE Trans. Software Eng., 2019

2018
Machine learning based code smell detection through WekaNose.
Proceedings of the 40th International Conference on Software Engineering: Companion Proceeedings, 2018

Towards an Architectural Debt Index.
Proceedings of the 44th Euromicro Conference on Software Engineering and Advanced Applications, 2018

2017
Code smell severity classification using machine learning techniques.
Knowl. Based Syst., 2017

Alternatives to the Knowledge Discovery Metamodel: An Investigation.
Int. J. Softw. Eng. Knowl. Eng., 2017

Model-Driven Reverse Engineering Approaches: A Systematic Literature Review.
IEEE Access, 2017

Arcan: A Tool for Architectural Smells Detection.
Proceedings of the 2017 IEEE International Conference on Software Architecture Workshops, 2017

Does the Migration to GitHub Relate to Internal Software Quality?.
Proceedings of the ENASE 2017, 2017

Change Prediction through Coding Rules Violations.
Proceedings of the 21st International Conference on Evaluation and Assessment in Software Engineering, 2017

2016
Comparing and experimenting machine learning techniques for code smell detection.
Empir. Softw. Eng., 2016

An Experience Report on Detecting and Repairing Software Architecture Erosion.
Proceedings of the 13th Working IEEE/IFIP Conference on Software Architecture, 2016

Antipattern and Code Smell False Positives: Preliminary Conceptualization and Classification.
Proceedings of the IEEE 23rd International Conference on Software Analysis, 2016

Tool support for evaluating architectural debt of an existing system: an experience report.
Proceedings of the 31st Annual ACM Symposium on Applied Computing, 2016

Smells Like Teen Spirit: Improving Bug Prediction Performance Using the Intensity of Code Smells.
Proceedings of the 2016 IEEE International Conference on Software Maintenance and Evolution, 2016

Technical Debt Indexes Provided by Tools: A Preliminary Discussion.
Proceedings of the 8th IEEE International Workshop on Managing Technical Debt, 2016

Automatic Detection of Instability Architectural Smells.
Proceedings of the 2016 IEEE International Conference on Software Maintenance and Evolution, 2016

2015
On applying machine learning techniques for design pattern detection.
J. Syst. Softw., 2015

A Duplicated Code Refactoring Advisor.
Proceedings of the Agile Processes, in Software Engineering, and Extreme Programming, 2015

On experimenting refactoring tools to remove code smells.
Proceedings of the Scientific Workshop Proceedings of the XP2015, 2015

Inter-smell relations in industrial and open source systems: A replication and comparative analysis.
Proceedings of the 2015 IEEE International Conference on Software Maintenance and Evolution, 2015

Towards a prioritization of code debt: A code smell Intensity Index.
Proceedings of the 7th IEEE International Workshop on Managing Technical Debt, 2015

Automatic Metric Thresholds Derivation for Code Smell Detection.
Proceedings of the 6th IEEE/ACM International Workshop on Emerging Trends in Software Metrics, 2015

Poster: Filtering Code Smells Detection Results.
Proceedings of the 37th IEEE/ACM International Conference on Software Engineering, 2015

Towards Assessing Software Architecture Quality by Exploiting Code Smell Relations.
Proceedings of the 2nd IEEE/ACM International Workshop on Software Architecture and Metrics, 2015

A Context-Aware Style of Software Design.
Proceedings of the 2nd IEEE/ACM International Workshop on Context for Software Development, 2015

2014
Pattern detection for conceptual schema recovery in data-intensive systems.
J. Softw. Evol. Process., 2014

A Refactoring Suggestion Tool for Removing Clones in Java Code.
ERCIM News, 2014

A System for the Discovery and Selection of FLOSS Projects.
ERCIM News, 2014

Capturing Software Evolution and Change through Code Repository Smells.
Proceedings of the Agile Methods. Large-Scale Development, Refactoring, Testing, and Estimation, 2014

Discover Knowledge on FLOSS Projects Through RepoFinder.
Proceedings of the KDIR 2014 - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval, Rome, Italy, 21, 2014

Tracking line changes in source code repositories.
Proceedings of the 2014 ACM-IEEE International Symposium on Empirical Software Engineering and Measurement, 2014

VCS-analyzer for software evolution empirical analysis.
Proceedings of the 2014 ACM-IEEE International Symposium on Empirical Software Engineering and Measurement, 2014

2013
Code Smell Detection: Towards a Machine Learning-Based Approach.
Proceedings of the 2013 IEEE International Conference on Software Maintenance, 2013

2012
Automatic detection of bad smells in code: An experimental assessment.
J. Object Technol., 2012

Code Smells, Micro Patterns and their Relations.
ERCIM News, 2012

A Benchmark for Design Pattern Detection Tools: a Community Driven Approach.
ERCIM News, 2012

DPB: A Benchmark for Design Pattern Detection Tools.
Proceedings of the 16th European Conference on Software Maintenance and Reengineering, 2012

2011
Using Design Pattern Clues to Improve the Precision of Design Pattern Detection Tools.
J. Object Technol., 2011

A tool for design pattern detection and software architecture reconstruction.
Inf. Sci., 2011

On Investigating Code Smells Correlations.
Proceedings of the Fourth IEEE International Conference on Software Testing, 2011

2010
Unifying Software and Data Reverse Engineering - A Pattern based Approach.
Proceedings of the ICSOFT 2010, 2010

A model proposal for program comprehension.
Proceedings of the 16th International Conference on Distributed Multimedia Systems, 2010

2008
Can design pattern detection be useful for legacy systemmigration towards SOA?
Proceedings of the 2nd International Workshop on Systems Development in SOA Environments, 2008


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