Marco Biazzini

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Hyper-heuristics (HHs) are heuristics that work with an arbitrary set of search operators or algorithms and combine these algorithms adaptively to achieve a better performance than any of the original heuristics. While HHs lend themselves naturally for distributed deployment, relatively little attention has been paid so far on the design and evaluation of(More)
Multi-repository software projects are becoming more and more popular, thanks to web-based facilities such as Github. Code and process metrics generally assume a single repository must be analyzed, in order to measure the characteristics of a codebase. Thus they are not apt to measure how much relevant information is hosted in multiple repositories(More)
Recent developments in the area of peer-to-peer (P2P) computing have enabled a new generation of fully-distributed global optimization algorithms via providing self-organizing control and load balancing mechanisms in very large scale, unreliable networks. Such decentralized networks (lacking a GRIDstyle resource management and scheduling infrastructure) are(More)
We introduce a generic framework for the distributed execution of combinatorial optimization tasks. Instead of relying on custom hardware (like dedicated parallel machines or clusters), our approach exploits, in a peer-to-peer fashion, the computing and storage power of existing, off-the- shelf desktops and servers. Contributions of this paper are a(More)
P2P-based optimization has recently gained interest among distributed function optimization scientists. Several well-known optimization heuristics have been recently re-designed to exploit the peculiarity of such a distributed environment. The final goal is to perform high quality function optimization by means of inexpensive, fully decentralized machines,(More)
Everyday, people use more and more digital resources (data, application systems, Internet, etc.) for all aspects of their life, like financial management, private exchanges, collaborative work, etc. This leads to non-negligible dependences on the digital distributed resources that reveal strong reliance at the social level. Users are often not aware of(More)
Empirical analysis of software repositories usually deals with linear histories derived from centralized versioning systems. Decentralized version control systems allow a much richer structure of commit histories, which presents features that are typical of complex graph models. In this paper we bring some evidences of how the very structure of these commit(More)
Distributed systems are getting more and more numerous, complex and used in a wide variety of applications. New solutions and new architectures arise (e.g., clouds) that support new functionalities (e.g., social networks) and pile up several software layers. This evolution implies new non negligible dependences among actors in the system (e.g., providers(More)
Peer-to-Peer (P2P) architectures are more and more used in recent content distribution platforms because of their valuable characteristics as scalability, performance, and negligible maintenance and distribution costs. In general, P2P applications allow users to provide preferences that are mainly related to performance, like number of connections and(More)
This thesis discusses the implementation of function optimization algorithms through distributed and decentralized processing in a peer-to-peer fashion. Our research is focused on a fully decentralized, general purpose P2P environment, with no special or ad-hoc facility for executing optimization tasks. Relevant information is exchanged among nodes by means(More)