Issues on Software Quality Models for Mastering Change

A promising cornerstone to master change and to continuously control software quality in the context of todays dynamically evolving complex software systems are software quality models. These models provide an abstract and analyzable view of software artifacts with the objective to describe, assess and/or predict quality. Although software quality models have a high potential to improve effectiveness and efficiency of quality assurance to cope with software change, their acceptance and spread in the software industry is still rather low, as there are several unresolved issues that have to be addressed by upcoming research. This article discusses and exemplifies unresolved key issues on descriptive, generating and predictive software quality models with regard to the (1) creation and maintenance of models, (2) support for extra-functional aspects, (3) traceability between quality models and unstructured artifacts, (4) integration of software analytics and runtime information, (5) balance between quality and risk, (6) process integration, as well as (7) justification by empirical evidence, and relates these issues to challenges of mastering change in terms of the manifesto of the LNCS Transactions on Foundations for Mastering Change.

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