Experimental Evaluation of a Tool for Change Impact Prediction in Requirements Models: Design, Results and Lessons Learned

There are commercial tools like IBM Rational RequisitePro and DOORS that support semi-automatic change impact analysis for requirements. These tools capture the requirements relations and allow tracing the paths they form. In most of these tools, relation types do not say anything about the meaning of the relations except the direction. When a change is introduced to a requirement, the requirements engineer analyzes the impact of the change in related requirements. In case semantic information is missing to determine precisely how requirements are related to each other, the requirements engineer generally has to assume the worst case dependencies based on the available syntactic information only. We developed a tool that uses formal semantics of requirements relations to support change impact analysis and prediction in requirements models. The tool TRIC (Tool for Requirements Inferencing and Consistency checking) works on models that explicitly represent requirements and the relations among them with their formal semantics. In this paper we report on the evaluation of how TRIC improves the quality of change impact predictions. A quasiexperiment is systematically designed and executed to empirically validate the impact of TRIC. We conduct the quasi-experiment with 21 master’s degree students predicting change impact for five change scenarios in a real software requirements specification. The participants are assigned with Microsoft Excel, IBM RequisitePro or TRIC to perform change impact prediction for the change scenarios. It is hypothesized that using TRIC would positively impact the quality of change impact predictions. Two formal hypotheses are developed. As a result of the experiment, we are not able to reject the null hypotheses, and thus we are not able to show experimentally the effectiveness of our tool. In the paper we discuss reasons for the failure to reject the null hypotheses in the experiment

Long-term survival and predictors of mortality in Coronat)' Heart Disease

Coronruy heart disease (CHD) is by far the most important cause of death, and a main cause of disability in the Netherlands. Accordingly, coronruy heart disease has a great impact on society. In 1995 cardiac death occurred in about 40,000 persons (28% of all monality) and ischemic heart disease was the reason for 170,000 hospital admissions. I Since the 1980s an inunediate benefit is achieved in patients with acute manifestations of CHD, with pharmacologic therapy such as thrombolytic therapy in patients with evolving myocru·dial infarction and coronary interventions such as coronary aorto bypass graft surgery (CABG) and percutaneous transluminal coronary angioplasty procedure (PTCA). Together with improved secondalY prevention through diet, reduced smoking and medical regimens such as antiplatelets, beta-blockers, ace-inhibitors and statins the life expectancy has been improved. This resulted in an increase of patients with chronic manifestations of CHD including heart failure and a population of survivors with a

Lessons from contemporary trials of cardiovascular prevention and rehabilitation: A systematic review and meta-analysis

Background: Meta-analyses of cardiac rehabilitation trials up to 2010 showed a significant reduction in all-cause mortality but many of these trials were conducted before the modern management of acute coronary syndromes. Methods: We undertook a meta-analysis of contemporary randomised controlled trials published in the period 2010 to 2015, including patients with other forms of atherosclerotic cardiovascular disease, to investigate the impact of cardiovascular prevention and rehabilitation on hard outcomes including survival. Results: 18 trials randomising 7691 patients to cardiovascular prevention and rehabilitation or usual care were selected. All-cause mortality was not reduced (RR 1.00, 95% CI 0.88 to 1.14), but cardiovascular mortality was by 58% (95% CI 0.21, 0.88). Myocardial infarction was also reduced by 30% (95% CI 0.54, 0.91) and cerebrovascular events by 60% (95% CI 0.22, 0.74). Comprehensive programmes managing six or more risk factors reduced all-cause mortality in a subgroup analysis (RR 0.63, 95% CI 0.43, 0.93) but those managing less did not. In the three programmes that prescribed and monitored cardioprotective medications for blood pressure and lipids all-cause mortality was also reduced (RR 0.35, 95% CI 0.18, 0.70). Conclusions: Comprehensive prevention and rehabilitation programmes managing six or more risk factors, and those prescribing and monitoring medications within programmes to lower blood pressure and lipids, continue to reduce all-cause mortality. In addition, these comprehensive programmes not only reduced cardiovascular mortality and myocardial infarction but also, for the first time, cerebrovascular events, and all these outcomes across a broader spectrum of patients with atherosclerotic disease