Dejanira Araiza-Illan

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This paper presents the deductive formal verification of high-level properties of control systems with theorem proving, using the Why3 tool. Properties that can be verified with this approach include stability, feedback gain, and robustness, among others. For the systems, modelled in Simulink, we propose three main steps to achieve the verification:(More)
Collaborative robots could transform several industries, such as manufacturing and healthcare, but they present a significant challenge to verification. The complex nature of their working environment necessitates testing in realistic detail under a broad range of circumstances. We propose the use of Coverage-Driven Verification (CDV) to meet this(More)
The widespread adoption of autonomous adaptive systems depends on provided guarantees of safety and functional correctness, at both design time and runtime. Specifying adaptive systems is cognitively difficult when their aspects are in a large number and have complicated dependencies. We present a technique to construct and automatically explore a(More)
Industries such as flexible manufacturing and home care will be transformed by the presence of robotic assistants. Assurance of safety and functional soundness for these robotic systems will require rigorous verification and validation. We propose testing in simulation using Coverage-Driven Verification (CDV) to guide the testing process in an automatic and(More)
This paper presents the verification of control systems implemented in Simulink. The goal is to ensure that high-level requirements on control performance, like stability, are satisfied by the Simulink diagram. A two stage process is proposed. First, the high-level requirements are decomposed into specific parametrized sub-requirements and implemented as(More)
We present an approach for the verification and validation (V\&V) of robot assistants in the context of human-robot interactions (HRI), to demonstrate their trustworthiness through integral assurances on their safety and functional correctness. Trust in robot assistants will allow them to transition from the laboratory into our everyday lives. The complex(More)
The widespread adoption of autonomous systems depends on providing guarantees of safety and functional correctness, at both design time and runtime. Information about the extent to which functional requirements can be met in combination with non-functional requirements (NFRs)–i.e. requirements that can be partially complied with–, under dynamic and(More)
The challenges of robotic software testing extend beyond conventional software testing. Valid, realistic and interesting tests need to be generated for multiple programs and hardware running concurrently, deployed into dynamic environments with people. We investigate the use of Belief-Desire-Intention (BDI) agents as models for test generation, in the(More)
The software of robotic assistants needs to be verified, to ensure its safety and functional correctness. Testing in simulation allows a high degree of realism in the verification. However, generating tests that cover both interesting foreseen and unforeseen scenarios in human-robot interaction (HRI) tasks, while executing most of the code, remains a(More)
Self-adaptive systems change their operational behaviour for instance to accommodate variations in their environment, while preserving functional requirements and maintaining acceptable conformance to non-functional requirements (NFRs). While conformance with functional requirements is clear-cut, it is more challenging to specify acceptable behaviours when(More)