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Monitoring and measuring the change-prediction process at different granularity levels: an empirical study

✍ Scribed by Mikael Lindvall


Publisher
John Wiley and Sons
Year
1998
Tongue
English
Weight
133 KB
Volume
4
Category
Article
ISSN
1077-4866

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✦ Synopsis


Monitoring and measuring industrial software processes are necessary for understanding processes and establishing baselines for process improvement. In this paper we monitor and measure the capability of experienced software developers to predict software change caused by new requirements to an existing software system (i.e. impact analysis) at different levels of granularity. The study shows a general underprediction and that the accuracy of the prediction deteriorated with increasing level of detail. The results were non-intuitive for the practitioners participating in the study and therefore important to consider when revising current processes and cost models based on such estimates. The study is a good example of how software industry can co-operate with university researchers in monitoring, measuring and evaluation of current practices. The results will be used by the organization as a baseline for further studies of subsequent releases of the product.