Visualizing and Measuring Software Portfolio Architectures: A Flexibility Analysis

Visualizing and Measuring Software Portfolio Architectures: A Flexibility Analysis by Robert Lagerstrom, Carliss Y. Baldwin, Alan MacCormack, and David Dreyfus

In this paper, we test a method for visualizing and measuring software portfolio architectures and use our measures to predict the costs of architectural change. Our data is drawn from a biopharmaceutical company, comprising 407 architectural components with 1,157 dependencies between them. We show that the architecture of this system can be classified as a “core-periphery” system, meaning it contains a single large dominant cluster of interconnected components (the “Core”) representing 32% of the system. We find that the classification of software applications within this architecture, as being either Core or Peripheral, is a significant predictor of the costs of architectural change. Using OLS regression models, we show that this measure has greater predictive power than prior measures of coupling used in the literature.

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