Integrated model for software component selection with simultaneous consideration of implementation and verification

One important objective of component-based software engineering is the minimization of the development cost of software products. Thus, the costs of software component implementation and verification, which may involve substantial expenses while under development, should be reduced. In addition, the costs for these processes should not be considered individually, but in an integrated manner, to further reduce development cost. In the current paper, an integrated decision model is proposed to assist decision-makers in selecting reuse scenarios for components used for implementation and in simultaneously determining the optimal number of test cases for verification. An objective of the model is the minimization of development cost, while satisfying the required system and reliability requirements. The Lagrange relaxation decomposition (LRD) method with heuristics was developed to solve integrated decision problems. Based on LRD, the nonlinear model is condensed into a 0-1 knapsack problem for the subproblem on reuse scenario selection and an integer knapsack problem for the subproblem on the determination of the optimal number of tests. Combined with the Lagrange multiplier-determined heuristic, the proposed algorithm can determine the global optimum solution. Simulations of varying sizes for problems and sensitivity analyses were conducted, and the results indicate that LRD is more effective than previous methods in determining global optimal solutions for the integrated decision problem. Highlights? An integrated decision model is proposed to select components reuse scenarios and determine the optimal number of test cases. ? An Objective of the model is to minimize development cost and satisfy the required system and reliability requirements. ? Lagrange relaxation decomposition (LRD) method with heuristics was developed to solve the integrated decision problem. ? Combined with the Lagrange multiplier-determined heuristic, the proposed algorithm can determine global optimum solution.