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Francesco Lomio
Francesco Lomio
Postdoctoral Researcher, Constructor Institute Schaffhausen
Verified email at constructor.org - Homepage
Title
Cited by
Cited by
Year
Are SonarQube Rules Inducing Bugs?
V Lenarduzzi, F Lomio, H Huttunen, D Taibi
27th IEEE International Conference on Software Analysis, Evolution and …, 2020
932020
Does migrating a monolithic system to microservices decrease the technical debt?
V Lenarduzzi, F Lomio, N Saarimäki, D Taibi
Journal of Systems and Software, 110710, 2020
852020
Software Quality for AI: Where we are now?
V Lenarduzzi, F Lomio, S Moreschini, D Taibi, DA Tamburri
International Conference on Software Quality (SWQD 2021), 2021
392021
Just-in-time software vulnerability detection: Are we there yet?
F Lomio, E Iannone, A De Lucia, F Palomba, V Lenarduzzi
Journal of Systems and Software 188, 111283, 2022
372022
Classification of Building Information Model (BIM) Structures with Deep Learning
F Lomio, R Farinha, M Laasonen, H Huttunen
2018 7th European Workshop on Visual Information Processing (EUVIP), 1-6, 2018
312018
Forecasting daily emergency department arrivals using high-dimensional multivariate data: a feature selection approach
J Tuominen, F Lomio, N Oksala, A Palomäki, J Peltonen, H Huttunen, ...
BMC medical informatics and decision making 22 (1), 134, 2022
202022
Fault Prediction based on Software Metrics and SonarQube Rules. Machine or Deep Learning?
F Lomio, S Moreschini, V Lenarduzzi
arXiv preprint arXiv:2103.11321, 2021
16*2021
MLOps for evolvable AI intensive software systems
S Moreschini, F Lomio, D Hästbacka, D Taibi
152022
Surface Type Classification for Autonomous Robot Indoor Navigation
F Lomio, E Skenderi, D Mohamadi, J Collin, R Ghabcheloo, H Huttunen
arXiv preprint arXiv:1905.00252, 2019
132019
PANDORA: Continuous Mining Software Repository and Dataset Generation
H Nguyen, F Lomio, F Pecorelli, V Lenarduzzi
IEEE International Conference on Software Analysis, Evolution and …, 2022
92022
RARE: a labeled dataset for cloud-native memory anomalies
F Lomio, DM Baselga, S Moreschini, H Huttunen, D Taibi
Proceedings of the 4th ACM SIGSOFT International Workshop on Machine …, 2020
82020
Regularity or Anomaly? On The Use of Anomaly Detection for Fine-Grained JIT Defect Prediction
F Lomio, L Pascarella, F Palomba, V Lenarduzzi
5*2022
Towards a Robust Approach to Analyze Time-Dependent Data in Software Engineering
N Saarimäki, S Moreschini, F Lomio, R Peñaloza, V Lenarduzzi
IEEE International Conference on Software Analysis, Evolution and …, 2022
52022
On The Benefits of the Accelerate Metrics: An Industrial Survey at Vendasta
F Lomio, Z Codabux, D Birth, D Hopkins, D Taibi
IEEE International Conference on Software Analysis, Evolution and …, 2022
32022
Metrics selection for load monitoring of service-oriented system
F Lomio, S Jurvansuu, D Taibi
Proceedings of the 5th International Workshop on Machine Learning Techniques …, 2021
32021
Anomaly Detection in Cloud-Native Systems
F Lomio, S Moreschini, X Li, V Lenarduzzi
1*
Predicting Failures of Autoscaling Distributed Applications
G DENARO, N EL MOUSSA, R HEYDAROV, F LOMIO, M PEZZÈ, K QIU
2024
Smart Edge Service Update Scheduler: An Industrial Use Case
S Moreschini, F Lomio, D Hästbacka, D Taibi
International Conference on Service-Oriented Computing, 171-182, 2022
2022
Machine Learning for Software Fault Detection: Issues and Possible Solutions
F Lomio
Tampere University, 2022
2022
On the Benefits of the Accelerate Metrics and Their Visualization: An Industrial Survey at Vendasta
F Lomio, Z Codabux, D Birtch, D Hopkins, D Taibi
Available at SSRN 4165880, 0
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