The Consequences of Variability in Software
I. Levendel
Abstract
I. Levendel
Abstract
Summary form only given. Contrary to many other industrial processes, software production is characterized by an unusually high variance. This directly results from the significant role of the human factor in all the phases of its realization, and this will likely remain the case for a long time to come. In order to set the record straight, this presentation first analyzes various aspects of software metrics that demonstrate the heterogeneous nature of software and the variance in the software production process. We propose a new software model susceptible to acknowledge software variance and take advantage of it for managing the software development process. This model allows the identification of areas of software instability that are caused by the concentration of software defects. Two major applications are derived from the model analysis. First, the model provides a method for evaluating the "goodness" of the software architecture. The model can also be used to balance the budgeting of the testing effort among the various software functionalities and their interactions. We also discuss potential applications of the recognition of software variability for developing reactive real-time methods for improving software dependability
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Summary form only given. Contrary to many other industrial processes, software production is characterized by an unusually high variance. This directly results from the significant role of the human factor in all the phases of its realization, and this will likely remain the case for a long time to come. In order to set the record straight, this presentation first analyzes various aspects of software metrics that demonstrate the heterogeneous nature of software and the variance in the software production process. We propose a new software model susceptible to acknowledge software variance and take advantage of it for managing the software development process. This model allows the identification of areas of software instability that are caused by the concentration of software defects. Two major applications are derived from the model analysis. First, the model provides a method for evaluating the "goodness" of the software architecture. The model can also be used to balance the budgeting of the testing effort among the various software functionalities and their interactions. We also discuss potential applications of the recognition of software variability for developing reactive real-time methods for improving software dependability
Key concepts: Computer science, Software construction, Software sizing, Software development, Software engineering, Software metric, Verification and validation, Software