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Recent breakthroughs in deep-learning (DL) approaches have resulted in the dynamic generation of trace links that are far more accurate than was previously possible. However, DL-generated links lack clear explanations, and therefore non-experts in the domain can find it difficult to understand the underlying semantics of the link, making it hard for them to evaluate the link's correctness or suitability for a specific software engineering task. In this paper we present a novel NLP pipeline for generating and visualizing trace link explanations. Our approach identifies domain-specific concepts, retrieves a corpus of concept-related sentences, mines concept definitions and usage examples, and identifies relations between cross-artifact concepts in order to explain the links. It applies a post-processing step to prioritize the most likely acronyms and definitions and to eliminate non-relevant ones. We evaluate our approach using project artifacts from three different domains of interstellar telescopes, positive train control, and electronic health-care systems, and then report coverage, correctness, and potential utility of the generated definitions. We design and utilize an explanation interface which leverages concept definitions and relations to visualize and explain trace link rationales, and we report results from a user study that was conducted to evaluate the effectiveness of the explanation interface. Results show that the explanations presented in the interface helped non-experts to understand the underlying semantics of a trace link and improved their ability to vet the correctness of the link.

BackgroundData on burden of peripheral artery disease (PAD) and its attributable risk factors are valuable for policymaking. We aimed to estimate the burden and risk factors for PAD from 1990 to 2019.MethodsWe extracted the data on prevalence, incidence, death, years lived with disability (YLDs), and years of life lost (YLLs) from the Global Burden of Disease Study 2019 to measure PAD burden. Moreover, the attributable burden to PAD risk factors was also estimated.ResultsGlobally, in 2019, 113,443,017 people lived with PAD and 10,504,092 new cases occurred, resulting in 74,063 deaths, 500,893 YLDs, and 1,035,487 YLLs. The absolute numbers of PAD prevalent and incident cases significantly increased between 1990 and 2019, contrasting with the decline trends in age-standardized prevalence and incidence rates. However, no statistically significant changes were detected in the global age-standardized death or YLL rates. The burden of PAD and its temporal trends varied significantly by location, gender, age group, and social-demographic status. Among all potentially modifiable risk factors, age-standardized PAD deaths worldwide were primarily attributable to high fasting plasma glucose, followed by high systolic blood pressure, tobacco, kidney dysfunction, diet high in sodium, and lead exposure.ConclusionPAD remained a serious public health problem worldwide. More strategies aimed at implementing cost-effective interventions and addressing modifiable risk factors should be carried out, especially in regions with high or increasing burden.