No abstract

No abstract

Most spreadsheets, like other software, change over time. A frequently occurring scenario is the repeated reuse and adaptation of spreadsheets from one project to another. If several versions of one spreadsheet for grading/budgeting/etc. have accumulated, it is often not obvious which one to choose for the next project. In situations like these, an understanding of how two versions of a spreadsheet differ is crucial to make an informed choice. Other scenarios are the reconciliation of two spreadsheets created by different users, generalizing different spreadsheets into a common template, or simply understanding and documenting the evolution of a spreadsheet over time.In this paper we present a method for identifying the changes between two spreadsheets with the explicit goal of presenting them to users in a concise form. We have implemented a prototype system, called SheetDiff, and tested the approach on several different spreadsheet pairs. As our evaluations will show, this system works reliably in practice. Moreover, we have compared SheetDiff to similar systems that are commercially available. An important difference is that while all these other tools distribute the change representation over two spreadsheets, our system displays all changes in the context of one spreadsheet, which results in a more compact representation.

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To meet quality-of-service requirements in changing environments, modern software systems adapt themselves. The structure, and correspondingly the behavior, of these systems undergoes continuous change. Model-driven performance engineering, however, assumes static system structures, behavior, and deployment. Hence, self-adaptive systems pose new challenges to model-driven performance engineering. There are a few surveys on self-adaptive systems, performance engineering, and the combination of both in the literature. In contrast to existing work, here we focus on model-driven performance analysis approaches. Based on a systematic literature review, we present a classification, identify open issues, and outline further research.