A genetic algorithm test generator

Use of a genetic algorithm and formal concept analysis to generate test data for branch coverage is explored in a prototype automatic test generator (ATG) called genet . genet is unique in the sense that it requires minimal source code instrumentation and analysis, and is programming language independent. Besides the novelty of using formal concept analysis within a genetic algorithm, genet extends the opportunism of another evolutionary ATG. Experiments were designed to evaluate the effectiveness of genet and the importance of selection in the evolution of test data. The results of the experiments indicate genet is most effective when selection plays a significant role. This is the case when test solutions for a program are necessarily organized. When it is not necessary for test solutions to resemble each other, adaptation appears to be the more dominant factor and the identification of suitable genetic operators becomes more important. Nevertheless, even in the latter situation, the presence of genet accelerated the evolutionary process for our test programs. Notwithstanding equal adaptation instructions, genetics mattered

Comparison of risk scoring systems for patients presenting with upper gastrointestinal bleeding: international multicentre prospective study

Objective: To compare the predictive accuracy and clinical utility of five risk scoring systems in the assessment of patients with upper gastrointestinal bleeding. Design: International multicentre prospective study. Setting: Six large hospitals in Europe, North America, Asia, and Oceania. Participants: 3012 consecutive patients presenting over 12 months with upper gastrointestinal bleeding. Main outcome measures: Comparison of pre-endoscopy scores (admission Rockall, AIMS65, and Glasgow Blatchford) and post-endoscopy scores (full Rockall and PNED) for their ability to predict predefined clinical endpoints: a composite endpoint (transfusion, endoscopic treatment, interventional radiology, surgery, or 30 day mortality), endoscopic treatment, 30 day mortality, rebleeding, and length of hospital stay. Optimum score thresholds to identify low risk and high risk patients were determined. Results: The Glasgow Blatchford score was best (area under the receiver operating characteristic curve (AUROC) 0.86) at predicting intervention or death compared with the full Rockall score (0.70), PNED score (0.69), admission Rockall score (0.66, and AIMS65 score (0.68) (all P<0.001). A Glasgow Blatchford score of ≤1 was the optimum threshold to predict survival without intervention (sensitivity 98.6%, specificity 34.6%). The Glasgow Blatchford score was better at predicting endoscopic treatment (AUROC 0.75) than the AIMS65 (0.62) and admission Rockall scores (0.61) (both P<0.001). A Glasgow Blatchford score of ≥7 was the optimum threshold to predict endoscopic treatment (sensitivity 80%, specificity 57%). The PNED (AUROC 0.77) and AIMS65 scores (0.77) were best at predicting mortality, with both superior to admission Rockall score (0.72) and Glasgow Blatchford score (0.64; P<0.001). Score thresholds of ≥4 for PNED, ≥2 for AIMS65, ≥4 for admission Rockall, and ≥5 for full Rockall were optimal at predicting death, with sensitivities of 65.8-78.6% and specificities of 65.0-65.3%. No score was helpful at predicting rebleeding or length of stay. Conclusions: The Glasgow Blatchford score has high accuracy at predicting need for hospital based intervention or death. Scores of ≤1 appear the optimum threshold for directing patients to outpatient management. AUROCs of scores for the other endpoints are less than 0.80, therefore their clinical utility for these outcomes seems to be limited. Trial registration: Current Controlled Trials ISRCTN16235737