Publications

Some publications can be found in the DBLP pages of:

Partial list of publications by year.

2021

2021 - Beyond Technical Aspects: How Do Community Smells Influence the Intensity of Code Smells?: Palomba, F., Tamburri, D., Arcelli Fontana, F., Oliveto, R., Zaidman, A., & Serebrenik, A. (2021). Beyond Technical Aspects: How Do Community Smells Influence the Intensity of Code Smells?. IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, 47(1 Jan. 1 2021), 108-129 [10.1109/TSE.2018.2883603].2021 - A systematic literature review on Technical Debt prioritization: Strategies, processes, factors, and tools: Lenarduzzi, V., Besker, T., Taibi, D., Martini, A., & Arcelli Fontana, F. (2021). A systematic literature review on Technical Debt prioritization: Strategies, processes, factors, and tools. THE JOURNAL OF SYSTEMS AND SOFTWARE, 171.2021 - An Overview and Comparison of Technical Debt Measurement Tools: Avgeriou, P., Taibi, D., Ampatzoglou, A., Arcelli Fontana, F., Besker, T., Chatzigeorgiou, A., et al. (2021). An Overview and Comparison of Technical Debt Measurement Tools. IEEE SOFTWARE, 38(3), 61-71 [10.1109/MS.2020.3024958].2021 - Internal Software Quality Evaluation of Self-adaptive Systems Using Metrics, Patterns, and Smells: Raibulet, C., Arcelli, F., & Carettoni, S. (2021). Internal Software Quality Evaluation of Self-adaptive Systems Using Metrics, Patterns, and Smells. In Evaluation of Novel Approaches to Software Engineering. 15th International Conference, ENASE 2020, Prague, Czech Republic, May 5–6, 2020, Revised Selected Papers (pp.386-419). Springer Science and Business Media Deutschland GmbH.2021 - Evaluating the Architectural Debt of IoT Projects: Fontana, F., & Pigazzini, I. (2021). Evaluating the Architectural Debt of IoT Projects. In 2021 IEEE/ACM 3rd International Workshop on Software Engineering Research and Practices for the IoT (SERP4IoT) (pp.27-31) [10.1109/SERP4IoT52556.2021.00011].2021 - A study on correlations between architectural smells and design patterns: Pigazzini, I., Arcelli Fontana, F., & Walter, B. (2021). A study on correlations between architectural smells and design patterns. THE JOURNAL OF SYSTEMS AND SOFTWARE, 178(August 2021) [10.1016/j.jss.2021.110984].2021 - Impact of Opportunistic Reuse Practices to Technical Debt: Capilla, R., Mikkonen, T., Carrillo, C., Arcelli Fontana, F., Pigazzini, I., & Lenarduzzi, V. (2021). Impact of Opportunistic Reuse Practices to Technical Debt. In Proceedings - 2021 IEEE/ACM International Conference on Technical Debt, TechDebt 2021 (pp.16-25). Institute of Electrical and Electronics Engineers Inc. [10.1109/TechDebt52882.2021.00011].2021 - The perception of Architectural Smells in industrial practice: Sas, D., Pigazzini, I., Avgeriou, P., & Arcelli Fontana, F. (2021). The perception of Architectural Smells in industrial practice. IEEE SOFTWARE [10.1109/MS.2021.3103664].2021 - DebtHunter: A machine learning-based approach for detecting self-admitted technical debt: Sala, I., Tommasel, A., & Arcelli Fontana, F. (2021). DebtHunter: A machine learning-based approach for detecting self-admitted technical debt. In ACM International Conference Proceeding Series (pp.278-283). Association for Computing Machinery [10.1145/3463274.3464455].

2020

2020 - A preliminary analysis of self-adaptive systems according to different issues: Raibulet, C., Arcelli Fontana, F., & Carettoni, S. (2020). A preliminary analysis of self-adaptive systems according to different issues. SOFTWARE QUALITY JOURNAL, 28(3), 1213-1243 [10.1007/s11219-020-09502-5].2020 - Improving change prediction models with code smell-related information: Catolino, G., Palomba, F., Arcelli, F., De Lucia, A., Zaidman, A., & Ferrucci, F. (2020). Improving change prediction models with code smell-related information. EMPIRICAL SOFTWARE ENGINEERING, 25(1), 49-95 [10.1007/s10664-019-09739-0].2020 - SAS vs. NSAS: Analysis and comparison of self-adaptive systems and non-self-adaptive systems based on smells and patterns: Raibulet, C., Arcelli, F., & Carettoni, S. (2020). SAS vs. NSAS: Analysis and comparison of self-adaptive systems and non-self-adaptive systems based on smells and patterns. In ENASE 2020 - Proceedings of the 15th International Conference on Evaluation of Novel Approaches to Software Engineering (pp.490-497). SciTePress.2020 - Sen4Smells: A tool for ranking sensitive smells for an architecture debt index: Diaz-Pace, J., Tommasel, A., Pigazzini, I., & Arcelli Fontana, F. (2020). Sen4Smells: A tool for ranking sensitive smells for an architecture debt index. In 2020 IEEE Congreso Bienal de Argentina, ARGENCON 2020 - 2020 IEEE Biennial Congress of Argentina, ARGENCON 2020 (pp.1-7). Institute of Electrical and Electronics Engineers Inc. [10.1109/ARGENCON49523.2020.9505535].

2019

2019 - Toward a Smell-aware Bug Prediction Model: Palomba, F., Zanoni, M., Arcelli Fontana, F., De Lucia, A., & Oliveto, R. (2019). Toward a Smell-aware Bug Prediction Model. IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, 45(2), 194-218 [10.1109/TSE.2017.2770122].2019 - PageRank and criticality of architectural smells: Fontana, F., Pigazzini, I., Raibulet, C., Basciano, S., & Roveda, R. (2019). PageRank and criticality of architectural smells. In ECSA '19 Proceedings of the 13th European Conference on Software Architecture - Volume 2 (pp.197-204). New York : Association for Computing Machinery [10.1145/3344948.3344982].2019 - Tool Support for the Migration to Microservice Architecture: An Industrial Case Study: Pigazzini, I., Arcelli Fontana, F., & Maggioni, A. (2019). Tool Support for the Migration to Microservice Architecture: An Industrial Case Study. In Software Architecture. 13th European Conference, ECSA 2019, Paris, France, September 9–13, 2019, Proceedings (pp.247-263) [10.1007/978-3-030-29983-5_17].2019 - Architectural smells detected by tools: A catalogue proposal: Azadi, U., Arcelli Fontana, F., & Taibi, D. (2019). Architectural smells detected by tools: A catalogue proposal. In Proceedings - 2019 IEEE/ACM International Conference on Technical Debt, TechDebt 2019 (pp.88-97). 345 E 47TH ST, NEW YORK, NY 10017 USA : Institute of Electrical and Electronics Engineers Inc. [10.1109/TechDebt.2019.00027].2019 - Investigating Instability Architectural Smells Evolution: An Exploratory Case Study: Sas, D., Avgeriou, P., & Arcelli Fontana, F. (2019). Investigating Instability Architectural Smells Evolution: An Exploratory Case Study. In Proceedings - 2019 IEEE International Conference on Software Maintenance and Evolution, ICSME 2019 (pp.557-567). Institute of Electrical and Electronics Engineers Inc. [10.1109/ICSME.2019.00090].2019 - Are architectural smells independent from code smells? An empirical study: Arcelli Fontana, F., Lenarduzzi, V., Roveda, R., & Taibi, D. (2019). Are architectural smells independent from code smells? An empirical study. THE JOURNAL OF SYSTEMS AND SOFTWARE, 154, 139-156 [10.1016/j.jss.2019.04.066].

2018

2018 - Collaborative and teamwork software development in an undergraduate software engineering course: Raibulet, C., & Arcelli Fontana, F. (2018). Collaborative and teamwork software development in an undergraduate software engineering course. THE JOURNAL OF SYSTEMS AND SOFTWARE, 144, 409-422 [10.1016/j.jss.2018.07.010].2018 - Towards an Architectural Debt Index: Roveda, R., Arcelli Fontana, F., Pigazzini, I., & Zanoni, M. (2018). Towards an Architectural Debt Index. In 2018 44th Euromicro Conference on Software Engineering and Advanced Applications (SEAA) (pp.408-416). IEEE [10.1109/SEAA.2018.00073].2018 - Code smells and their collocations: A large-scale experiment on open-source systems: Walter, B., Arcelli Fontana, F., & Ferme, V. (2018). Code smells and their collocations: A large-scale experiment on open-source systems. THE JOURNAL OF SYSTEMS AND SOFTWARE, 144, 1-21 [10.1016/j.jss.2018.05.057].2018 - An architectural smells detection tool for C and C++ projects: Biaggi, A., Arcelli Fontana, F., & Roveda, R. (2018). An architectural smells detection tool for C and C++ projects. In Proceedings - 44th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2018 (pp.417-420). 345 E 47TH ST, NEW YORK, NY 10017 USA : Institute of Electrical and Electronics Engineers Inc. [10.1109/SEAA.2018.00074].2018 - How do community smells influence code smells?: Palomba, F., Tamburri, D., Serebrenik, A., Zaidman, A., Arcelli Fontana, F., & Oliveto, R. (2018). How do community smells influence code smells?. In ICSE '18 Proceedings of the 40th International Conference on Software Engineering: Companion Proceeedings (pp.240-241). 345 E 47TH ST, NEW YORK, NY 10017 USA : IEEE Computer Society [10.1145/3183440.3194950].2018 - Machine learning based code smell detection through WekaNose: Azadi, U., Arcelli Fontana, F., & Zanoni, M. (2018). Machine learning based code smell detection through WekaNose. In ICSE '18 Proceedings of the 40th International Conference on Software Engineering: Companion Proceeedings (pp.288-289). 345 E 47TH ST, NEW YORK, NY 10017 USA : IEEE Computer Society [10.1145/3183440.3194974].2018 - Automatic detection of sources and sinks in arbitrary Java libraries: Sas, D., Bessi, M., & Arcelli Fontana, F. (2018). Automatic detection of sources and sinks in arbitrary Java libraries. In Proceedings - 18th IEEE International Working Conference on Source Code Analysis and Manipulation, SCAM 2018 (pp.103-112). Institute of Electrical and Electronics Engineers Inc. [10.1109/SCAM.2018.00019].2018 - Support for architectural smell refactoring: Rizzi, L., Arcelli Fontana, F., & Roveda, R. (2018). Support for architectural smell refactoring. In IWoR 2018 Proceedings of the 2nd International Workshop on Refactoring (pp.7-10). ACM [10.1145/3242163.3242165].

2017

2017 - An Overview on Quality Evaluation of Self-Adaptive Systems: Raibulet, C., Arcelli Fontana, F., Capilla, R., & Carrillo, C. (2017). An Overview on Quality Evaluation of Self-Adaptive Systems. In I. Mistrik, N. Ali, R. Kazman, J. Grundy, & B. Schmerl (a cura di), Managing Trade-Offs in Adaptable Software Architectures (pp. 325-352). Elsevier.2017 - Automatic detection of instability architectural smells: Arcelli Fontana, F., Pigazzini, I., Roveda, R., & Zanoni, M. (2017). Automatic detection of instability architectural smells. In Proceedings of the 32nd International Conference on Software Maintenance and Evolution (ICSME 2016) (pp.433-437). Raleigh : Institute of Electrical and Electronics Engineers Inc. [10.1109/ICSME.2016.33].2017 - Smells like teen spirit: Improving bug prediction performance using the intensity of code smells: Palomba, F., Zanoni, M., Arcelli Fontana, F., De Lucia, A., & Oliveto, R. (2017). Smells like teen spirit: Improving bug prediction performance using the intensity of code smells. In Proceedings of the 32nd International Conference on Software Maintenance and Evolution (ICSME 2016) (pp.244-255). Institute of Electrical and Electronics Engineers Inc. [10.1109/ICSME.2016.27].2017 - Does the migration to GitHub relate to internal software quality?: Roveda, R., Arcelli Fontana, F., Raibulet, C., Zanoni, M., & Rampazzo, F. (2017). Does the migration to GitHub relate to internal software quality?. In Proceedings of the 12th International Conference on Evaluation of Novel Approaches to Software Engineering 2017 (pp.293-300). SciTePress [10.5220/0006367402930300].2017 - Students' feedback in using GitHub in a project development for a software engineering course: Arcelli Fontana, F., & Raibulet, C. (2017). Students' feedback in using GitHub in a project development for a software engineering course. In ACM Proceedings of the 22nd Annual Conference on Innovation and Technology in Computer Science Education (pp.380-380). Association for Computing Machinery [10.1145/3059009.3072984].2017 - IEEE International Workshop on Machine Learning Techniques for Software Quality Evaluation: Arcelli Fontana, F., Walter, B., & Zanoni, M. (2017). IEEE International Workshop on Machine Learning Techniques for Software Quality Evaluation. In IEEE International Workshop on Machine Learning Techniques for Software Quality Evaluation. Institute of Electrical and Electronics Engineers Inc..2017 - Arcan: A tool for architectural smells detection: Arcelli Fontana, F., Pigazzini, I., Roveda, R., Tamburri, D., Zanoni, M., & Nitto, E. (2017). Arcan: A tool for architectural smells detection. In Proceeding of the International Conference On Software Architecture (ICSA 2017) IEEE (pp.282-285). Gothemburg : Institute of Electrical and Electronics Engineers Inc. [10.1109/ICSAW.2017.16].2017 - Change prediction through coding rules violations: Tollin, I., Arcelli Fontana, F., Zanoni, M., & Roveda, R. (2017). Change prediction through coding rules violations. In ACM Proceedings of the 21th International Conference on Evaluation and Assessment in Software Engineering (EASE) (pp.61-64). Karlskrona : Association for Computing Machinery [10.1145/3084226.3084282].2017 - Code smell severity classification using machine learning techniques: Arcelli Fontana, F., & Zanoni, M. (2017). Code smell severity classification using machine learning techniques. KNOWLEDGE-BASED SYSTEMS, 128, 43-58 [10.1016/j.knosys.2017.04.014].2017 - Alternatives to the Knowledge Discovery Metamodel: An Investigation: Arcelli Fontana, F., Raibulet, C., & Zanoni, M. (2017). Alternatives to the Knowledge Discovery Metamodel: An Investigation. INTERNATIONAL JOURNAL OF SOFTWARE ENGINEERING AND KNOWLEDGE ENGINEERING, 27(7), 1097-1128 [10.1142/S0218194017500413].2017 - Model-driven reverse engineering approaches: A systematic literature review: Raibulet, C., Arcelli Fontana, F., & Zanoni, M. (2017). Model-driven reverse engineering approaches: A systematic literature review. IEEE ACCESS, 5, 14516-14542 [10.1109/ACCESS.2017.2733518].2017 - Evaluation of self-Adaptive systems: A women perspective: Raibulet, C., & Arcelli Fontana, F. (2017). Evaluation of self-Adaptive systems: A women perspective. In Proceedings of the 11th European Conference on Software Architecture: Companion Proceedings (pp.23-30). Association for Computing Machinery.2017 - Ninth international workshop on managing technical debt report on the MTD 2017 workshop: Arcelli Fontana, F., Trumler, W., Izurieta, C., & Nord, R. (2017). Ninth international workshop on managing technical debt report on the MTD 2017 workshop. In ACM International Conference Proceeding Series (pp.1-3). Association for Computing Machinery [10.1145/3120459.3120461].2017 - Technical Debt in Agile Development: Report on the Ninth Workshop on Managing Technical Debt: ARCELLI FONTANA, F., Chatzigeorgiou, A., Trumler, W., Izurieta, C., Avgeriou, P., & Nord, R. (2017). Technical Debt in Agile Development: Report on the Ninth Workshop on Managing Technical Debt. SOFTWARE ENGINEERING NOTES, 42(3), 18-21.

2016

2016 - Anti-pattern and code smell false positives: Preliminary conceptualisation and classification: Arcelli Fontana, F., Dietrich, J., Walter, B., Yamashita, A., & Zanoni, M. (2016). Anti-pattern and code smell false positives: Preliminary conceptualisation and classification. In Proceedings of the 23rd IEEE International Conference on Software Analysis, Evolution, and Reengineering (SANER 2016) (pp.609-613). Institute of Electrical and Electronics Engineers Inc. [10.1109/SANER.2016.84].2016 - Tool support for evaluating architectural debt of an existing system: An experience report: Arcelli Fontana, F., Roveda, R., & Zanoni, M. (2016). Tool support for evaluating architectural debt of an existing system: An experience report. In Proceedings of the 31st ACM/SIGAPP Symposium on Applied Computing (SAC 2016) (pp.1347-1349). Association for Computing Machinery [10.1145/2851613.2851963].2016 - An experience report on detecting and repairing software architecture erosion: Arcelli Fontana, F., Roveda, R., Zanoni, M., Raibulet, C., & Capilla, R. (2016). An experience report on detecting and repairing software architecture erosion. In Proceedings of the 13th Working IEEE/IFIP Conference on Software Architecture (WICSA 2016) (pp.21-30). Institute of Electrical and Electronics Engineers Inc. [10.1109/WICSA.2016.37].2016 - On evaluating the impact of the refactoring of architectural problems on software quality: Arcelli Fontana, F., Roveda, R., Vittori, S., Metelli, A., Saldarini, S., & Mazzei, F. (2016). On evaluating the impact of the refactoring of architectural problems on software quality. In Proceedings of the Scientific Workshop Proceedings of XP2016 (pp.1-8). Edimburg : Association for Computing Machinery [10.1145/2962695.2962716].2016 - Technical Debt Indexes Provided by Tools: A Preliminary Discussion: Arcelli Fontana, F., Roveda, R., & Zanoni, M. (2016). Technical Debt Indexes Provided by Tools: A Preliminary Discussion. In Proceedings of the 8th International Workshop on Managing Technical Debt (MTD 2016) (pp.28-31). Raleigh : Institute of Electrical and Electronics Engineers Inc. [10.1109/MTD.2016.11].2016 - Comparing and experimenting machine learning techniques for code smell detection: Arcelli Fontana, F., Mäntylä, M., Zanoni, M., & Marino, A. (2016). Comparing and experimenting machine learning techniques for code smell detection. EMPIRICAL SOFTWARE ENGINEERING, 21(3), 1143-1191 [10.1007/s10664-015-9378-4].