Madonna With a Heart Scarred As a Face With Bad Maybe Smallpox

Aunque las pruebas de mutación son una técnica bien conocida para evaluar la calidad de las pruebas, no hay mucho apoyo disponible para el análisis de mutaciones a nivel de modelo. También se considera costoso debido a: (i) la gran cantidad de mutantes generados; (ii) la actividad lenta de determinar mutantes equivalentes; y (iii) el tiempo de ejecución mutante. También debe recordarse que los artefactos de software reales de tamaño apropiado, incluyendo fallas reales, son difíciles de encontrar y preparar adecuadamente. En este artículo, proponemos una herramienta de mutación para generar mutantes de primer orden (FOM) válidos para esquemas conceptuales (CS) basados ​​en diagramas de clase UML y evaluar su efectividad y eficiencia en la generación de mutantes válidos y no equivalentes. Nuestros principales hallazgos fueron: (1 ) Los operadores de mutación FOM pueden automatizarse para evitar mutantes no válidos (49,1%). (2) Se generaron menos mutantes equivalentes (7,2%) y el 74,3% se redujo analizando la estructura estática de CS en seis CS de sujeto. © Springer International Publishing Suiza 2017.Although mutation testing is a well-known technique for assessing the quality of tests, there is not a lot of support available for model-level mutation analysis. It is also considered to be expensive due to: (i) the large number of mutants generated; (ii) the time-consuming activity of determining equivalent mutants; and (iii) the mutant execution time. It should also be remembered that real software artefacts of appropriate size including real faults are hard to find and prepare appropriately. In this paper we propose a mutation tool to generate valid First Order Mutants (FOM) for Conceptual Schemas (CS) based on UML Class Diagrams and evaluate its effectiveness and efficiency in generating valid and non-equivalent mutants.Our main findings were: (1) FOM mutation operators can be automated to avoiding non-valid mutants (49.1%). (2) Fewer equivalent mutants were generated (7.2%) and 74.3% were reduced by analysing the CS static structure in six subject CSs. © Springer International Publishing Switzerland 2017.Katowic

Coverage-based quality metric of mutation operators for test suite improvement

The choice of mutation operators is a fundamental aspect in mutation testing to guide the tester to an effective test suite. Designing a set of mutation operators is subject to a trade-off between effectiveness and computational cost: a larger mutation population might uncover more faults, but will take longer to analyse. With the aim of resolving this trade-off, several authors have defined an assortment of metrics to determine the most valuable operators. In this work, we extend an existing quality metric by incorporating an additional source of data and coverage information and therefore investigate the extent to which mutants that are often covered but rarely killed can improve the evaluation of mutation operators for the refinement of the test suite. As a case study, we analyse C++ class-level operators based on the new coverage-based quality metric to assess whether the original metric is enhanced. The results when selecting the best-valued operators show that this metric has great potential to help the tester in finding effective mutation operators. In comparison with the metric from which it is derived, the use of coverage data allows to reduce the number of mutants but often loses fewer test cases and, in addition, retains those that seem hard to design

A global collaboRAtive study of CIC-rearranged, BCOR::CCNB3-rearranged and other ultra-rare unclassified undifferentiated small round cell sarcomas (GRACefUl)

[Background] Undifferentiated small round cell sarcomas (URCSs) represent a diagnostic challenge, and their optimal treatment is unknown. We aimed to define the clinical characteristics, treatment, and outcome of URCS patients.[Methods] URCS patients treated from 1983 to 2019 at 21 worldwide sarcoma reference centres were retrospectively identified. Based on molecular assessment, cases were classified as follows: (1) CIC-rearranged round cell sarcomas, (2) BCOR::CCNB3-rearranged round cell sarcomas, (3) unclassified URCSs. Treatment, prognostic factors and outcome were reviewed.[Results] In total, 148 patients were identified [88/148 (60%) CIC-rearranged sarcoma (median age 32 years, range 7–78), 33/148 (22%) BCOR::CCNB3-rearranged (median age 17 years, range 5–91), and 27/148 (18%) unclassified URCSs (median age 37 years, range 4–70)]. One hundred-one (68.2%) cases presented with localised disease; 47 (31.8%) had metastases at diagnosis. Male prevalence, younger age, bone primary site, and a low rate of synchronous metastases were observed in BCOR::CCNB3-rearranged cases. Local treatment was surgery in 67/148 (45%) patients, and surgery + radiotherapy in 52/148 (35%). Chemotherapy was given to 122/148 (82%) patients. At a 42.7-month median follow-up, the 3-year overall survival (OS) was 92.2% (95% CI 71.5–98.0) in BCOR::CCNB3 patients, 39.6% (95% CI 27.7–51.3) in CIC-rearranged sarcomas, and 78.7% in unclassified URCSs (95% CI 56.1–90.6; p < 0.0001).[Conclusions] This study is the largest conducted in URCS and confirms major differences in outcomes between URCS subtypes. A full molecular assessment should be undertaken when a diagnosis of URCS is suspected. Prospective studies are needed to better define the optimal treatment strategy in each URCS subtype.This work was supported by the Carisbo Foundation Call for Translational and Clinical Medical Research.Peer reviewe

SARS-CoV-2 vaccination modelling for safe surgery to save lives: data from an international prospective cohort study

Background: Preoperative SARS-CoV-2 vaccination could support safer elective surgery. Vaccine numbers are limited so this study aimed to inform their prioritization by modelling. Methods: The primary outcome was the number needed to vaccinate (NNV) to prevent one COVID-19-related death in 1 year. NNVs were based on postoperative SARS-CoV-2 rates and mortality in an international cohort study (surgical patients), and community SARS-CoV-2 incidence and case fatality data (general population). NNV estimates were stratified by age (18-49, 50-69, 70 or more years) and type of surgery. Best- and worst-case scenarios were used to describe uncertainty. Results: NNVs were more favourable in surgical patients than the general population. The most favourable NNVs were in patients aged 70 years or more needing cancer surgery (351; best case 196, worst case 816) or non-cancer surgery (733; best case 407, worst case 1664). Both exceeded the NNV in the general population (1840; best case 1196, worst case 3066). NNVs for surgical patients remained favourable at a range of SARS-CoV-2 incidence rates in sensitivity analysis modelling. Globally, prioritizing preoperative vaccination of patients needing elective surgery ahead of the general population could prevent an additional 58 687 (best case 115 007, worst case 20 177) COVID-19-related deaths in 1 year. Conclusion: As global roll out of SARS-CoV-2 vaccination proceeds, patients needing elective surgery should be prioritized ahead of the general population