The Case for Quantitative Process Management

Authors:
Bill Curtis;Girish V. Seshagiri;Donald Reifer;Iraj Hirmanpour;Gargi Keeni
Affiliations:
CAST Software;Advanced Information Services;Reifer Consultants;Software Engineering Intitute;Tata Consultancy Services
Venue:
IEEE Software
Year:
2008

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Abstract

This article introduces a special section on "Embedding Statistical Methods into Software Engineering Practices." It provides a background on Quantitative Process Management and makes the case for why these methods are important. It presents an example of how a model can be developed to predict project outcomes by using data emerging from the performance of process tasks. It discusses how these methods can be used with different software development paradigms. It ends by summarizing develops needed in five different communities in order for these methods to be widely adopted.