In this paper we present a correlational study in which we assess the ability of five size measures to predict the number of changes to requirements 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 of number of changes. 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 projects for five measures of size of requirements (number of actors, use cases, words, lines, and revisions), we have built and evaluated prediction models for number of changes to requirements. 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. We performed a cross systems validation. For our best model we calculated a pred(0.25)=0.5, which is better than the accuracy of common effort prediction models like for example COCOMO. 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 developer perception are unreliable. Predictions models, like the one presented here can help to mitigate that risk.

This paper is a summary of a PhD thesis which describes our effort to define and validate requirements volatility measures. These measures have been proven to be reliable predictors of requirements volatility. 1. TECHNICAL PROBLEM Since requirements often change, even during development, it is important to predict the continuing definition of requirements as they change throughout the software life cycle to be able to anticipate and respond to requests of change. The consequences of poor management of changes would be higher project costs, risks for schedule slippage, and decrease in quality. These consequences could lead to project failure. Even though there are high risks in managing requirements, this is in general not done properly. In a survey of 4000 European companies it was found that the management of customer requirements was one of the main problem areas in software development. Among the requirements management (RM) activities, measuring and predicting volatility is very important. High volatility can cause cost and schedule overruns, making the goals of the project hard to achieve. Numerous software measures for the RM activities and for requirements volatility have been proposed in the literature. To our knowledge, none of them have been validated. The goal of this research is therefore to define and validate requirements measures, proving that they can be used as reliable predictors of requirements volatility. 2. CONTRIBUTIONS AND METHODS USED We defined a general and wide set of 38 measures for the management of requirements [3]. The measures were obtained by applying the Goal Question Metrics paradigm to the RM Key Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee.

Software requirements are the initial step in a software development cycle. Gathering requirements and managing requirements well are key factors to a successful software project. Many software projects have failed because of poor requirements. Nowadays software requirements is a very hot topic in software industry. This thesis describes metrics that are useful to the requirements manager as they allow to establish an effective communication between the development team and the customer, to manage the requirements phases effectively and efficiently and to produce a quality end product. Using the metrics proposed in this thesis, the requirements manager can easily improve the management of requirements and set goals for the organization to achieve maximum quality in the end product.