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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)
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 GRID-style resource management and scheduling infrastructure)(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)
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)
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)
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)
Scientists working in the area of distributed function optimization have to deal with a huge variety of optimization techniques and algorithms. Most of the existing research in this domain makes use of tightly-coupled systems that either have strict synchronization requirements or completely rely on a central server, which coordinates the work of clients(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). They pile up several software layers and, given that any software is directly dependent of the underlying layers, it can be unable to(More)
Peer-to-Peer (P2P) architectures are more and more used in Content Delivery Networks (CDN), because the traditional client-server architectures are burdened by high distribution and maintenance cost, whereas in P2P systems those costs are almost negligible. In general, such applications do not take into account user preferences, other than QoS-related(More)