Automated estimation of predictive object points metric values for object-oriented code

Abstract

If we are to improve the OO software quality we develop, we must measure our designs by well-defined standards. Possible problems in our system designs can be detected during the development process. If we are to estimate and manage our efforts, we must measure our progress effectively. An object-oriented coding scheme is, in some ways, incompatible with ancient metrics. To measure the size of software system, a variety of techniques for code development estimation exist like SLOC and Function Point, SLOC, as a metric has a number of drawbacks one is SLOC, is not consistent across languages, applications, or developing environments, however, it cannot applied on object-oriented code. The efforts required to develop the code is being calculated using the Predictive Object Point (POP) metric. This counting technique is supported by the Function Point Technique. This paper address the way of effort calculation for object oriented code using POP. To measure the POP accurately, an automated tool has been developed and designed. The results of the tools has also been discussed in the paper.