摘要
Software reverse engineering and reengineering techniques are most often applied to reconstruct the software archi-tecture with respect to quality constraints, or non-functional requirements such as maintainability or reusability. In this paper, the performance improvement of distributed software is modeled as a search problem that is solved by heuristic search algorithms such as genetic search methods. To achieve this, firstly, all aspects of the distributed execution of a software is specified by an analytical performance evaluation function that not only evaluates the current deployment of the software from the performance perspective but also can be applied to propose the near-optimal object deploy-ment for that software. This analytical function is applied as the Heuristic search objective function. In this paper a novel statement reordering method is also presented which is used to generate the search objective function such that the best solution in the search space can be found.
Software reverse engineering and reengineering techniques are most often applied to reconstruct the software archi-tecture with respect to quality constraints, or non-functional requirements such as maintainability or reusability. In this paper, the performance improvement of distributed software is modeled as a search problem that is solved by heuristic search algorithms such as genetic search methods. To achieve this, firstly, all aspects of the distributed execution of a software is specified by an analytical performance evaluation function that not only evaluates the current deployment of the software from the performance perspective but also can be applied to propose the near-optimal object deploy-ment for that software. This analytical function is applied as the Heuristic search objective function. In this paper a novel statement reordering method is also presented which is used to generate the search objective function such that the best solution in the search space can be found.
