Safety-critical applications often use dependability cases to validate that specified properties are invariant, or to demonstrate a counter example showing how that property might be violated. However, most dependability cases are written with a single product in mind. At the same time, software product lines (families of related software products) have been studied with the goal of modeling variability and commonality, and building family based techniques for both analysis and testing. However, there has been little work on building an end to end dependability case for a software product line (where a property is modeled, a counter example is found and then validated as a true positive via testing), and none that we know of in an emerging safety-critical domain, that of robotic surgery. In this paper, we study a family of surgical robots, that combine hardware and software, and are highly configurable, representing over 1300 unique robots. At the same time, they are considered safety-critical and should have associated dependability cases. We perform a case study to understand how we can bring together lightweight formal analysis, feature modeling, and testing to provide an end to end pipeline to find potential violations of important safety properties. In the process, we learned that there are some interesting and open challenges for the research community, which if solved will lead towards more dependable safety-critical cyber-physical systems. CCS CONCEPTS • Software and its engineering → Software defect analysis; Formal software verification; Model-driven software engineering;

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Automated test generation techniques for graphical user interfaces include model-based approaches that generate tests from a graph or state machine model, capture-replay methods that require the user to demonstrate each test case, and pattern-based approaches that provide templates for abstract test cases. There has been little work, however, in automated goal-based testing, where the goal is a realistic user task, a function, or an abstract behavior. Recent work in human performance regression testing has shown that there is a need for generating multiple test cases that execute the same user task in different ways, however that work does not have an efficient way to generate tests and only a single type of goal has been considered. In this paper we expand the notion of goal based interface testing to generate tests for a variety of goals. We develop a direct test generation technique, EventFlowSlicer, that is more efficient than that used in human performance regression testing, reducing run times by 92.5% on average for test suites between 9 to 26 steps and 63.1% across all test suites. Our evaluation shows that the number of tests generated is non-trivial-more than can be easily captured manually. On average EventFlowSlicer generated 38 test cases per suite, and as many as 200 test cases which all achieve the same goal for a specified task. CCS Concepts •Software and its engineering → Software verification and validation;

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