Selecting Modules to be Preferentially Reviewed Using Integer Programming Approach

Abstract

There has been considerable research on Fault-Prone (FP) module prediction using software metrics, and their findings would be useful in the plan for reviewing and testing the modules. Toward a practical application of the FP module prediction methods, this paper focuses on the optimal selection of modules to be preferentially reviewed from a cost-effectiveness standpoint, since practitioners face some real constraints on the development time and cost. The paper considers a fault-proneness of a module to be the worth reviewing the module, and proposes to formulate the optimal selection of modules to be reviewed, as a 0-1 integer programming problem, i.e., knapsack problem. The empirical work using 500 sample modules from NASA IV & V shows the proposed method would be better than conventional one on the cost-effectiveness.