A Correlational Study on Four Size Measures as Predictors of Requirements Volatility

Requirements volatility is an important risk factor for software projects. Software measures can help in quantifying and predicting this risk. In this paper, we present a correlational study with the goal of predicting requirements volatility for a medium size software project. The study is explorative, i.e. we analyse the data collected for our measures to find out the best predictor. To our knowledge, no empirical validation of requirements change measures as predictors has been performed in an industrial setting. Based on the data collected from two industrial software projects for four measures of size of requirements (number of actors, use cases, words, and lines), we have built and evaluated prediction models for requirements volatility. These models can help project managers to estimate the volatility of requirements and minimize the risks caused by volatile requirements, like schedule and costs overruns. Performing a cross systems validation, the best model showed a MMRE= 0.25, which can be considered reliable. Although our models are likely to have only local validity, the general method for constructing the prediction models could be applied in any software development company. In an earlier study, we showed that decisions solely based on developers’ perception of requirements volatility are unreliable. Predictions models, like the one presented here, can therefore help taking more reliable decisions.