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Trustworthiness of software and services is a key concern for their use and adoption by organizations and endusers. Trustworthiness evaluation is an important task to support making informed decisions for both providers and consumers, i.e., for selecting components from a software marketplace. An analysis of the state of the art in software evaluation technologies motivated us to develop an evidence-based approach for trustworthiness evaluation. Most of the literature evaluates trustworthiness by focusing on a single dimension (e.g., from the security perspective) while there are limited contributions towards multifaceted and end-to-end trustworthiness evaluation. Our analysis reveals that there is a lack of a comprehensive framework for comparative, multi-faceted end-to-end trustworthiness evaluation, which takes into account different layers of abstractions of both the system topology and its trustworthiness. In this paper, we provide a framework for endto-end trustworthiness evaluation using computational approaches, which is based on aggregating certified trustworthiness values for individual components. The resulted output supports in the definition of trustworthiness requirements for a software component to be locally developed and eventually integrated within a system, as well as, trustworthiness evidences for a composite system before the actual deployment. Thereby supports the designer in analyzing the end-to-end trustworthiness values. An application example illustrates the application of the framework.

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Collaborative Embedded Systems (CES) typically operate in highly dynamic contexts that cannot be completely predicted during design time. These systems are subject to a wide range of uncertainties occurring at runtime, which can be distinguished in aleatory or epistemic. While aleatory uncertainty refers to stochasticity that is present in natural or physical processes and systems, epistemic uncertainty refers to the knowledge that is available to the system, for example, in the form of an ontology, being insufficient for the functionalities that require certain knowledge. Even though both of these two kinds of uncertainties are relevant for CES, epistemic uncertainties are especially important, since forming Collaborative System Groups (CSGs) requires a structured exchange of information. In the au