{'fraction_non_alphanumeric': 0.0194601381042059, 'fraction_numerical': 0.0, 'mean_word_length': 5.559670781893004, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Model-Based Continuous Verification

Model-based engineering has emerged as a key set of technologies to engineer software systems. While system source code is expected to match with the designed model, legacy systems and workarounds during deployment would undoubtedly change the source code, making the actual running implementation mismatch with its model. Such mismatch poses a challenge of maintaining the conformance between the model and the corresponding implementation. Prior techniques, such as model checking and model-based testing, simply assumed the sole correctness of the model or the implementation, which is naive since they both could contain correct information (e.g. representing either the software requirements or the actual running environment).In this paper, we aim to address this problem through model-based continuous verification (ConV), an iterative verification process that links the traditional model checking phase with the software testing phase to a feedback loop, ensuring the conformance between the system model and its implementation. It allows to execute the abstract test cases over the implementation through a semi-automatic binding mechanism to guide the update of the code, and augments system properties from the actually running system to guide the update of the model through model checking. Based on these techniques, we implemented Eunomia, a conformance verification system, to support the continuous verification process. Experiments show that Eunomia can effectively detect and locate inconsistencies both in the model and the source code.