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 | 500 | 2016 |
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 | 301 | 2012 |
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 | 213 | 2013 |
Code smell severity classification using machine learning techniques FA Fontana, M Zanoni Knowledge-Based Systems 128, 43-58, 2017 | 184 | 2017 |
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 | 166 | 2021 |
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 | 155 | 2017 |
On applying machine learning techniques for design pattern detection M Zanoni, FA Fontana, F Stella Journal of Systems and Software 103, 102-117, 2015 | 145 | 2015 |
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 | 139 | 2018 |
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 | 132 | 2015 |
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 | 131 | 2017 |
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 | 127 | 2020 |
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 | 122 | 2011 |
A tool for design pattern detection and software architecture reconstruction FA Fontana, M Zanoni Information sciences 181 (7), 1306-1324, 2011 | 119 | 2011 |
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 | 114 | 2015 |
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 | 107 | 2019 |
Automatic detection of instability architectural smells FA Fontana, I Pigazzini, R Roveda, M Zanoni 2016 IEEE international conference on software maintenance and evolution …, 2016 | 107 | 2016 |
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 | 96 | 2016 |
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 | 96 | 2012 |
Model-driven reverse engineering approaches: A systematic literature review C Raibulet, FA Fontana, M Zanoni Ieee Access 5, 14516-14542, 2017 | 95 | 2017 |
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 | 85 | 2013 |