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Francesca Arcelli Fontana
Francesca Arcelli Fontana
Professore Ordinario
Adresă de e-mail confirmată pe disco.unimib.it - Pagina de pornire
Titlu
Citat de
Citat de
Anul
Comparing and experimenting machine learning techniques for code smell detection
F Arcelli Fontana, MV Mäntylä, M Zanoni, A Marino
Empirical Software Engineering 21, 1143-1191, 2016
4382016
Automatic detection of bad smells in code: An experimental assessment.
FA Fontana, P Braione, M Zanoni
J. Object Technol. 11 (2), 5:1-38, 2012
2862012
Code smell detection: Towards a machine learning-based approach
FA Fontana, M Zanoni, A Marino, MV Mäntylä
2013 IEEE international conference on software maintenance, 396-399, 2013
1992013
Code smell severity classification using machine learning techniques
FA Fontana, M Zanoni
Knowledge-Based Systems 128, 43-58, 2017
1602017
Arcan: A tool for architectural smells detection
FA Fontana, I Pigazzini, R Roveda, D Tamburri, M Zanoni, E Di Nitto
2017 IEEE International Conference on Software Architecture Workshops (ICSAW …, 2017
1352017
On applying machine learning techniques for design pattern detection
M Zanoni, FA Fontana, F Stella
Journal of Systems and Software 103, 102-117, 2015
1332015
A systematic literature review on technical debt prioritization: Strategies, processes, factors, and tools
V Lenarduzzi, T Besker, D Taibi, A Martini, FA Fontana
Journal of Systems and Software 171, 110827, 2021
1312021
Toward a smell-aware bug prediction model
F Palomba, M Zanoni, FA Fontana, A De Lucia, R Oliveto
IEEE Transactions on Software Engineering 45 (2), 194-218, 2017
1212017
Beyond technical aspects: How do community smells influence the intensity of code smells?
F Palomba, DA Tamburri, FA Fontana, R Oliveto, A Zaidman, ...
IEEE transactions on software engineering 47 (1), 108-129, 2018
1192018
Towards a prioritization of code debt: A code smell intensity index
FA Fontana, V Ferme, M Zanoni, R Roveda
2015 IEEE 7th International Workshop on Managing Technical Debt (MTD), 16-24, 2015
1182015
A tool for design pattern detection and software architecture reconstruction
FA Fontana, M Zanoni
Information sciences 181 (7), 1306-1324, 2011
1162011
An experience report on using code smells detection tools
FA Fontana, E Mariani, A Mornioli, R Sormani, A Tonello
2011 IEEE fourth international conference on software testing, verification …, 2011
1142011
Automatic metric thresholds derivation for code smell detection
FA Fontana, V Ferme, M Zanoni, A Yamashita
2015 IEEE/ACM 6th International Workshop on Emerging Trends in Software …, 2015
1042015
An overview and comparison of technical debt measurement tools
PC Avgeriou, D Taibi, A Ampatzoglou, FA Fontana, T Besker, ...
Ieee software 38 (3), 61-71, 2020
1012020
Automatic detection of instability architectural smells
FA Fontana, I Pigazzini, R Roveda, M Zanoni
2016 IEEE International Conference on Software Maintenance and Evolution …, 2016
972016
Architectural smells detected by tools: a catalogue proposal
U Azadi, FA Fontana, D Taibi
2019 IEEE/ACM International Conference on Technical Debt (TechDebt), 88-97, 2019
962019
Investigating the impact of code smells debt on quality code evaluation
FA Fontana, V Ferme, S Spinelli
2012 Third International Workshop on Managing Technical Debt (MTD), 15-22, 2012
902012
Antipattern and code smell false positives: Preliminary conceptualization and classification
FA Fontana, J Dietrich, B Walter, A Yamashita, M Zanoni
2016 IEEE 23rd international conference on software analysis, evolution, and …, 2016
872016
Investigating the impact of code smells on system's quality: An empirical study on systems of different application domains
FA Fontana, V Ferme, A Marino, B Walter, P Martenka
2013 IEEE International Conference on Software Maintenance, 260-269, 2013
792013
Model-driven reverse engineering approaches: A systematic literature review
C Raibulet, FA Fontana, M Zanoni
Ieee Access 5, 14516-14542, 2017
772017
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