Francesco Lomio

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 22

Top Topics

Anomaly Detection

Manually Labeled

Emergency Department

Top Venues

J. Syst. Softw.

Publications

Giovanni Denaro, Noura El Moussa, Rahim Heydarov, Francesco Lomio, Mauro Pezzè, Ketai Qiu
Predicting Failures of Autoscaling Distributed Applications. Proc. ACM Softw. Eng. 1 (FSE) (2024)
Francesco Lomio, Sergio Moreschini, Valentina Lenarduzzi
A machine and deep learning analysis among SonarQube rules, product, and process metrics for fault prediction. Empir. Softw. Eng. 27 (7) (2022)
Sergio Moreschini, Francesco Lomio, David Hästbacka, Davide Taibi
Smart Edge Service Update Scheduler: An Industrial Use Case. ICSOC Workshops (2022)
Jalmari Tuominen, Francesco Lomio, Niku Oksala, Ari Palomäki, Jaakko Peltonen, Heikki Huttunen, Antti Roine
Forecasting daily emergency department arrivals using high-dimensional multivariate data: a feature selection approach. BMC Medical Informatics Decis. Mak. 22 (1) (2022)
Francesco Lomio, Zadia Codabux, Dale Birtch, Dale Hopkins, Davide Taibi
On the Benefits of the Accelerate Metrics: An Industrial Survey at Vendasta. SANER (2022)
Hung Nguyen, Francesco Lomio, Fabiano Pecorelli, Valentina Lenarduzzi
PANDORA: Continuous Mining Software Repository and Dataset Generation. SANER (2022)
Francesco Lomio, Emanuele Iannone, Andrea De Lucia, Fabio Palomba, Valentina Lenarduzzi
Just-in-time software vulnerability detection: Are we there yet? J. Syst. Softw. 188 (2022)
Sergio Moreschini, Francesco Lomio, David Hästbacka, Davide Taibi
MLOps for evolvable AI intensive software systems. SANER (2022)
Nyyti Saarimäki, Sergio Moreschini, Francesco Lomio, Rafael Peñaloza, Valentina Lenarduzzi
Towards a Robust Approach to Analyze Time-Dependent Data in Software Engineering. SANER (2022)
Francesco Lomio, Sergio Moreschini, Xiaozhou Li, Valentina Lenarduzzi
Anomaly Detection in Cloud-Native Systems. SEAA (2022)
Francesco Lomio, Luca Pascarella, Fabio Palomba, Valentina Lenarduzzi
Regularity or Anomaly? On The Use of Anomaly Detection for Fine-Grained JIT Defect Prediction. SEAA (2022)
Valentina Lenarduzzi, Francesco Lomio, Sergio Moreschini, Davide Taibi, Damian Andrew Tamburri
Software Quality for AI: Where We Are Now? SWQD (2021)
Francesco Lomio, Sergio Moreschini, Valentina Lenarduzzi
Fault Prediction based on Software Metrics and SonarQube Rules. Machine or Deep Learning? CoRR (2021)
Francesco Lomio, Sampsa Jurvansuu, Davide Taibi
Metrics selection for load monitoring of service-oriented system. MaLTeSQuE@ESEC/SIGSOFT FSE (2021)
Francesco Lomio, Diego Martínez Baselga, Sergio Moreschini, Heikki Huttunen, Davide Taibi
RARE: a labeled dataset for cloud-native memory anomalies. MaLTeSQuE@ESEC/SIGSOFT FSE (2020)
Valentina Lenarduzzi, Francesco Lomio, Nyyti Saarimäki, Davide Taibi
Does migrating a monolithic system to microservices decrease the technical debt? J. Syst. Softw. 169 (2020)
Valentina Lenarduzzi, Francesco Lomio, Heikki Huttunen, Davide Taibi
Are SonarQube Rules Inducing Bugs? SANER (2020)
Francesco Lomio, Erjon Skenderi, Damoon Mohamadi, Jussi Collin, Reza Ghabcheloo, Heikki Huttunen
Surface Type Classification for Autonomous Robot Indoor Navigation. CoRR (2019)
Valentina Lenarduzzi, Francesco Lomio, Davide Taibi, Heikki Huttunen
On the Fault Proneness of SonarQube Technical Debt Violations: A comparison of eight Machine Learning Techniques. CoRR (2019)
Nyyti Saarimäki, Francesco Lomio, Valentina Lenarduzzi, Davide Taibi
Does Migrate a Monolithic System to Microservices Decreases the Technical Debt? CoRR (2019)
Francesco Lomio, Ricardo Farinha, Mauri Laasonen, Heikki Huttunen
Classification of Building Information Model (BIM) Structures with Deep Learning. CoRR (2018)
Francesco Lomio, Ricardo Farinha, Mauri Laasonen, Heikki Huttunen
Classification of Building Information Model (BIM) Structures with Deep Learning. EUVIP (2018)