Library Miniaturization Using Static and Dynamic Information

Moving to smaller libraries can be considered as a relevant task when porting software systems to limited-resource devices (e.g., hand-helds). Library miniaturization will be particularly effective if based on both dynamic (keeping into account dependencies exploited during application execution in a given user profile) and static (keeping into account all possible dependencies) information. This paper presents a distributed software architecture, based on web services, to collect dynamic information at run-time, and an approach for miniaturization of libraries, exploiting both dynamic and static information with the aim of reducing the memory requirements of executables. New, smaller libraries are identified via hierarchical clustering and genetic algorithms; clustering produces a first initial solution, then optimized by multi-objective genetic algorithms. The approach has been applied to medium size open source software systems such as Samba and MySQL, allowing to effectively produce smaller, loosely coupled libraries, and to reduce the memory requirements of each application.