Towards efficient optimization in package management systems

Package management as a means of reuse of software artifacts has become extremely popular, most notably in Linux distributions. At the same time, successful package management brings about a number of computational challenges. Whenever a user requires a new package to be installed, a package manager not only installs the new package but it might also install other packages or uninstall some old ones in order to respect dependencies and conflicts of the packages. Coming up with a new configuration of packages is computationally challenging. It is in particular complex when we also wish to optimize for user preferences, such as that the resulting package configuration should not differ too much from the original one. A number of exact approaches for solving this problem have been proposed in recent years. These approaches, however, do not have guaranteed runtime due to the high computational complexity of the problem. This paper addresses this issue by devising a hybrid approach that integrates exact solving with approximate solving by invoking the approximate part whenever the solver is running out of time. Experimental evaluation shows that this approach enables returning high-quality package configurations with rapid response time.