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Learn

Learning From Failing and Passing Executions At the Speed of Internet

Total Cost €

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EC-Contrib. €

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Partnership

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Project "Learn" data sheet

The following table provides information about the project.

Coordinator
UNIVERSITA' DEGLI STUDI DI MILANO-BICOCCA 

Organization address
address: PIAZZA DELL'ATENEO NUOVO 1
city: MILANO
postcode: 20126
website: www.unimib.it

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Italy [IT]
 Project website http://www.lta.disco.unimib.it/Learn/
 Total cost 1˙141˙875 €
 EC max contribution 1˙141˙875 € (100%)
 Programme 1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
 Code Call ERC-2014-CoG
 Funding Scheme ERC-COG
 Starting year 2015
 Duration (year-month-day) from 2015-10-01   to  2019-09-30

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    UNIVERSITA' DEGLI STUDI DI MILANO-BICOCCA IT (MILANO) coordinator 1˙141˙875.00

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 Project objective

Modern software systems must be extremely flexible and easily adaptable to different user needs and environments. However, this flexibility also introduces relevant quality issues. These problems are so common that is sufficient browsing the Web to find millions of reports about failures observed after updates and incompatibilities caused by the interaction of a newly installed component with the existing components.

The impact of problems introduced by end-users can be dramatic because end-users can easily modify applications, like developers do, but end-users have neither the knowledge nor the skill of developers, and they cannot debug and fix the problems that they unintentionally introduce. It is thus necessary to timely develop novel solutions that can increase the reliability of the moderns systems, which can be extended and adapted by end-users, with the capability to automatically address problems that are unknown at development-time.

The Learn project aims to produce innovative solutions for the development of systems that can work around the problems introduced by end-users when modifying their applications. The three key elements introduced by Learn to automatically produce a (temporary) fix for the software are: (1) the definition of the InternetLearn infrastructure, which is a network infrastructure that enables communication between every individual instance of a same program running at different end-users’ sites, thus augmenting each application with the capability to access a huge amount of information collected in-the-field from other sites; (2) the definition of analysis techniques that can learn the characteristics of successful and failed runs by monitoring executions in the field from a number of instances running at many end-user sites; and (3) the definition of techniques for the automatic generation and actuation of temporary fixes on an Internet (World) scale.

 Publications

year authors and title journal last update
List of publications.
2020 Leonardo Mariani, Mauro Pezzè, Oliviero Riganelli, Rui Xin
Predicting Failures in Multi-Tier Distributed Systems
published pages: , ISSN: 0164-1212, DOI:
Journal of Systems and Software 2020-02-07
2018 Oliviero Riganelli, Daniela Micucci, Leonardo Mariani
From source code to test cases: A comprehensive benchmark for resource leak detection in Android apps
published pages: 540-548, ISSN: 0038-0644, DOI: 10.1002/spe.2672
Software: Practice and Experience 49/3 2020-02-07
2020 Oliviero Riganelli, Daniela Micucci, Leonardo Mariani
Controlling Interactions with Libraries in Android Apps ThroughRuntime Enforcement
published pages: , ISSN: 1556-4665, DOI:
ACM Transactions on Autonomous and Adaptive Systems (TAAS) 2020-02-07
2019 Oscar Cornejo, Davide Ginelli, Daniela Briola, Daniela Micucci, Leonardo Mariani
Field Monitoring With Delayed Saving
published pages: 85913-85924, ISSN: 2169-3536, DOI: 10.1109/access.2019.2925855
IEEE Access 7 2020-02-07
2019 Marco Mobilio, Oliviero Riganelli, Daniela Micucci, Leonardo Mariani
FILO: FIx-LOcus Recommendation for ProblemsCaused by Android Framework Upgrade
published pages: , ISSN: , DOI:
Proceedings of the International Symposium on Software Reliability Engineering (ISSRE) 2020-02-07
2017 Oliviero Riganelli, Daniela Micucci, Leonardo Mariani, Yliès Falcone
Verifying Policy Enforcers
published pages: 241-258, ISSN: , DOI: 10.1007/978-3-319-67531-2_15
Proceedings of the International Conference on Runtime Verification (RV) Annual 2020-02-07
2017 Oscar Cornejo, Daniela Briola, Daniela Micucci, Leonardo Mariani
Fragmented Monitoring
published pages: 57-68, ISSN: 2075-2180, DOI: 10.4204/EPTCS.254.5
Electronic Proceedings in Theoretical Computer Science 254 2020-02-07
2016 Leonardo Mariani, Mauro Pezze, Mauro Santoro
GK-Tail+ An Efficient Approach to Learn Software Models
published pages: 1-1, ISSN: 0098-5589, DOI: 10.1109/TSE.2016.2623623
IEEE Transactions on Software Engineering 2020-02-07
2017 Luca Gazzola, Daniela Micucci, Leonardo Mariani
Automatic Software Repair: A Survey
published pages: 1-1, ISSN: 0098-5589, DOI: 10.1109/TSE.2017.2755013
IEEE Transactions on Software Engineering Monthly 2020-02-07
2018 Daniela Briola, Daniela Micucci, Leonardo Mariani
A platform for P2P agent-based collaborative applications
published pages: , ISSN: 0038-0644, DOI: 10.1002/spe.2657
Software: Practice and Experience 2020-02-07
2018 Sina Shamshiri, José Miguel Rojas, Luca Gazzola, Gordon Fraser, Phil McMinn, Leonardo Mariani, Andrea Arcuri
Random or evolutionary search for object-oriented test suite generation?
published pages: e1660, ISSN: 0960-0833, DOI: 10.1002/stvr.1660
Software Testing, Verification and Reliability 28/4 2020-02-07
2018 Luca Gazzola, Daniela Micucci, Leonardo Mariani
Automatic Software Repair: A Survey
published pages: 1219, ISSN: , DOI:
Proceedings of the International Conference on Software Engineering 2020-02-07

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