Do software models based on the UML aid in source-code comprehensibility? Aggregating evidence from 12 controlled experiments

In this paper, we present the results of long-term research conducted in order to study the contribution made by software models based on the Unified Modeling Language (UML) to the comprehensibility of Java source-code deprived of comments. We have conducted 12 controlled experiments in different experimental contexts and on different sites with participants with different levels of expertise (i.e., Bachelor’s, Master’s, and PhD students and software practitioners from Italy and Spain). A total of 333 observations were obtained from these experiments. The UML models in our experiments were those produced in the analysis and design phases. The models produced in the analysis phase were created with the objective of abstracting the environment in which the software will work (i.e., the problem domain), while those produced in the design phase were created with the goal of abstracting implementation aspects of the software (i.e., the solution/application domain). Source-code comprehensibility was assessed with regard to correctness of understanding, time taken to accomplish the comprehension tasks, and efficiency as regards accomplishing those tasks. In order to study the global effect of UML models on source-code comprehensibility, we aggregated results from the individual experiments using a meta-analysis. We made every effort to account for the heterogeneity of our experiments when aggregating the results obtained from them. The overall results suggest that the use of UML models affects the comprehensibility of source-code, when it is deprived of comments. Indeed, models produced in the analysis phase might reduce source-code comprehensibility, while increasing the time taken to complete comprehension tasks. That is, browsing source code and this kind of models together negatively impacts on the time taken to complete comprehension tasks without having a positive effect on the comprehensibility of source code. One plausible justification for this is that the UML models produced in the analysis phase focus on the problem domain. That is, models produced in the analysis phase say nothing about source code and there should be no expectation that they would, in any way, be beneficial to comprehensibility. On the other hand, UML models produced in the design phase improve source-code comprehensibility. One possible justification for this result is that models produced in the design phase are more focused on implementation details. Therefore, although the participants had more material to read and browse, this additional effort was paid back in the form of an improved comprehension of source code

Left atrial volume during stress is associated with increased risk of arrhythmias in patients with hypertrophic cardiomyopathy

Introduction: In patients affected by hypertrophic cardiomyopathy (HCM), left atrial volume index (LAVi) is associated with an increased risk of tachyarrhythmias and major clinical events. To date, the clinical meaning of LAVi measured during exercise (stress LAVi [sLAVi]) has not yet been investigated in HCM. This study sought to evaluate the correlation between LAVi/sLAVi and clinical outcome (risk of arrhythmias and heart failure [HF]) in patients with HCM. Methods and Results: We enrolled a total of 51 consecutive patients with HCM (39 men; mean age: 39.41 ± 17.9 years) who underwent standard and stress echocardiography, following a common protocol. During follow-up (median follow-up was 1.82 years), the following composite endpoints were collected: ARRHYT endpoint (atrial fibrillation, paroxysmal supraventricular tachycardia, nonsustained ventricular tachycardia (VT), sustained VT, ventricular fibrillation, syncope of likely cardiogenic nature, and sudden cardiac death) and HF endpoint (worsening of functional class and left ventricular ejection fraction, hospitalization, and death for end-stage HF). Eight patients were lost at follow-up. ARRHYT endpoint occurred in 13 (30.2%) patients (8, 18.6%, supraventricular and 10, 23.2%, ventricular arrhythmias), whereas HF endpoint occurred in 5 (11.6%) patients. sLAVi (mean value of 31.16 ± 10.15 mL/m2) performed better than rLAVi as a predictor of ARRHYT endpoint (Akaike Information Criterion: 48.37 vs. 50.37, if dichotomized according to the median values). A sLAVi value of 30 mL/m2 showed a predictive accuracy of 72.1% (C-statistics of 0.7346), with a high negative predictive value (87.5%). Conclusion: These findings encourage future studies on sLAVi, as a potential predictor of arrhythmias and adverse outcome in patients with HCM

Clinical and genetic characterization of patients with hypertrophic cardiomyopathy and right atrial enlargement

AIMS: Prevalence and clinical significance of right atrial enlargement (RAE) has been poorly characterized in hypertrophic cardiomyopathy. METHODS: One hundred and sixty consecutive patients with hypertrophic cardiomyopathy (35.5 ± 20 years; 64% men) were studied. They underwent clinical examination, standard ECG, M-mode, 2D and Doppler echocardiography, stress test and ECG Holter monitoring. Major adverse cardiac events were considered: cardiac death (sudden death, heart failure death); cardiac transplant; resuscitated cardiac arrest or appropriate implantable cardioverter defibrillator discharge. Genetic analysis of eight sarcomeric genes was performed using Sanger sequencing. RESULTS: RAE was observed in 22 patients (14%), associated with left atrial enlargement in all cases. Patients with RAE were likely to have restrictive mitral pattern (P < 0.001) and had higher New York Heart Association (P < 0.001), N-terminal prohormone of brain natriuretic peptide (P < 0.001), left atrial volume index (P < 0.001), lateral (P = 0.04) and septal (P = 0.002) E/e', systolic pulmonary artery pressure (P < 0.001) and lower ejection fraction (all P < 0.001). On cardiopulmonary exercise testing, peak VO2 was lower and VE/VCO2 higher in patients with RAE (P < 0.001). During a mean follow-up of 4 ± 2.1 years, 30 major adverse cardiac events in 24 patients (15%) were observed. Cox proportional hazards regression analysis identified RAE as an independent predictor of major adverse cardiac events (odds ratio = 2.6; confidence interval 1.5-4.6; P = 0.001). In patients with RAE who were genetically tested, there was a higher prevalence of sarcomeric gene mutations (68%), double mutations (16%) and troponin T mutations (21%). CONCLUSION: RAE is present in a small subset of patients with hypertrophic cardiomyopathy, and largely reflects increased pulmonary pressures because of severe diastolic and/or systolic left ventricular dysfunction. Patients with RAE had a higher prevalence of sarcomeric gene mutations, troponin T mutations and complex genotypes. In conclusion, RAE may serve as a very useful marker of disease progression and adverse outcome in patients with sarcomeric hypertrophic cardiomyopathy

Prevalence and clinical significance of red flags in patients with hypertrophic cardiomyopathy

Introduction: We sought to determine prevalence and predictive accuracy of clinical markers (red flags, RF), known to be associated with specific systemic disease in a consecutive cohort of patients with hypertrophic cardiomyopathy (HCM). / Methods: We studied 129 consecutive patients (23.7 ± 20.9 years, range 0–74 years; male/female 68%/32%). Pre-specified RF were categorized into five domains: family history; signs/symptoms; electrocardiography; imaging; and laboratory. Sensitivity (Se), specificity (Sp), negative predictive value (NPV), positive predictive value (PPV), and predictive accuracy of RF were analyzed in the genotyped population. / Results: In the overall cohort of 129 patients, 169 RF were identified in 62 patients (48%). Prevalence of RF was higher in infants (78%) and in adults >55 years old (58%). Following targeted genetic and clinical evaluation, 94 patients (74%) had a definite diagnosis (sarcomeric HCM or specific causes of HCM). We observed 14 RF in 13 patients (21%) with sarcomeric gene disease, 129 RF in 34 patients (97%) with other specific causes of HCM, and 26 RF in 15 patients (45%) with idiopathic HCM (p  55yo. Se, Sp, PPV, NPV and PA of RF were 97%, 70%, 55%, 98% and 77%, respectively. Single and clinical combination of RF (clusters) had an high specificity, NPV and predictive accuracy for the specific etiologies (syndromes/metabolic/infiltrative disorders associated with HCM). / Conclusions: An extensive diagnostic work up, focused on analysis of specific diagnostic RF in patients with unexplained LVH facilitates a clinical diagnosis in 74% of patients with HCM

The Usability of E-learning Platforms in Higher Education: A Systematic Mapping Study

The use of e-learning in higher education has increased significantly in recent years, which has led to several studies being conducted to investigate the usability of the platforms that support it. A variety of different usability evaluation methods and attributes have been used, and it has therefore become important to start reviewing this work in a systematic way to determine how the field has developed in the last 15 years. This paper describes a systematic mapping study that performed searches on five electronic libraries to identify usability issues and methods that have been used to evaluate e-learning platforms. Sixty-one papers were selected and analysed, with the majority of studies using a simple research design reliant on questionnaires. The usability attributes measured were mostly related to effectiveness, satisfaction, efficiency, and perceived ease of use. Furthermore, several research gaps have been identified and recommendations have been made for further work in the area of the usability of online learning

Using the normalized levenshtein distance to analyze relationship between faults and local variables with confusing names: A further investigation

This paper exploits further uses of NLD (Normalized Levenshtein Distance), proposed in a recent study, to quantify the level of confusion of variables with the aim of verifying if they can provide indications about the presence of faults. We provide further evidence that fault prediction models based on the considered NLD measures can provide accurate estimations

The geography of innovation dynamics

Cities and metropolitan areas are major drivers of creativity and innovation in all possible sectors: scientific, technological, social, artistic, etc. The critical concentration and proximity of diverse mindsets and opportunities, supported by efficient infrastructures, enable new technologies and ideas to emerge, thrive, and trigger further innovation. Though this pattern seems well established, geography’s role in the emergence and diffusion of new technologies still needs to be clarified. An additional important question concerns the identification of the innovation pathways of metropolitan areas. Here, we explore the factors that influence the spread of technology among metropolitan areas worldwide and how geography and political borders impact this process. Our evidence suggests that political geography has been highly important for the diffusion of innovation till around two decades ago, slowly declining afterwards in favour of a more global innovation ecosystem. Further, the visualisation of the evolution of countries and metropolitan areas in a 2d space of competitiveness and diversification reveals the existence of two main innovation pathways, discriminating between different strategies towards progress. Our work provides insights for policymakers seeking to promote economic growth and technological advancement through tailored investments in prioritarian innovation areas