Stability and resource allocation in project planning.

The majority of resource-constrained project scheduling efforts assumes perfect information about the scheduling problem to be solved and a static deterministic environment within which the pre-computed baseline schedule is executed. In reality, project activities are subject to considerable uncertainty, which generally leads to numerous schedule disruptions. In this paper, we present a resource allocation model that protects a given baseline schedule against activity duration variability. A branch-and-bound algorithm is developed that solves the proposed resource allocation problem. We report on computational results obtained on a set of benchmark problems.Constraint satisfaction; Information; Model; Planning; Problems; Project management; Project planning; Project scheduling; Resource allocati; Scheduling; Stability; Uncertainty; Variability;

Recognizing design patterns in C++ programs with the integration of Columbus and Maisa

A method for recognizing design patterns from C++ programs is presented. The method consists of two separate phases, analysis and reverse engineering of the C++ code, and architectural pattern matching over the reverse-engineered intermediate code representation. It is shown how the pattern recognition effect can be realized by integrating two specialized software tools, the reverse engineering framework Columbus and the architectural metrics analyzer Maisa. The method and the integrated power of the tool set are illustrated with small experiments