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Tobias Pett

Publications and source records attributed to Tobias Pett.

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Improving Communication of Changes in Model-Based Engineering with Model-Independent Change Descriptions

In model-based engineering, inter-disciplinary teams collaborate through models, which change over time for purposes of system development, what makes the proper description of such changes crucial for engineers. However, any change made by the engineer of one discipline will be difficult to understand by the engineers of other disciplines. To overcome this limitation, model-independent change descriptions can be derived instead, which preserve semantics of the changes and do not require model-specific knowledge. The two opposing approaches here are to describe changes using either informal language or formal notions of change. While informal language lacks objectivity and standardisation, formal notions of change lack human interpretability, and thus offering no support for inter-disciplinary communication. In this paper, we propose functions to map formally specified changes, represented in the approach of delta modelling, to change descriptions in model-independent language. In an exhaustive mixed-methods evaluation, we bridge the gap between the theoretical and the practical representation of changes. We quantitatively assess technical feasibility, with an implementation framework, and technical applicability, along a case study; and we qualitatively assess plausibility, practical applicability, and extensibility, in a user study. Our work shows a promising starting point for automated, model-independent description of changes in model-based engineering projects.

cs.SE

MulTi-Wise Sampling: Trading Uniform T-Wise Feature Interaction Coverage for Smaller Samples

Ensuring the functional safety of highly configurable systems often requires testing representative subsets of all possible configurations to reduce testing effort and save resources. The ratio of covered t-wise feature interactions (i.e., T-Wise Feature Interaction Coverage) is a common criterion for determining whether a subset of configurations is representative and capable of finding faults. Existing t-wise sampling algorithms uniformly cover t-wise feature interactions for all features, resulting in lengthy execution times and large sample sizes, particularly when large t-wise feature interactions are considered (i.e., high values of t). In this paper, we introduce a novel approach to t-wise feature interaction sampling, questioning the necessity of uniform coverage across all t-wise feature interactions, called \emph{\mulTiWise{}}. Our approach prioritizes between subsets of critical and non-critical features, considering higher t-values for subsets of critical features when generating a t-wise feature interaction sample. We evaluate our approach using subject systems from real-world applications, including \busybox{}, \soletta{}, \fiasco{}, and \uclibc{}. Our results show that sacrificing uniform t-wise feature interaction coverage between all features reduces the time needed to generate a sample and the resulting sample size. Hence, \mulTiWise{} Sampling offers an alternative to existing approaches if knowledge about feature criticality is available.

cs.SE