Facet classification of software quality measures

Cybernetics ◽  
1990 ◽  
Vol 25 (4) ◽  
pp. 546-563
Author(s):  
G. P. Kozhevnikova ◽  
A. A. Stognii
Keyword(s):  
Software Quality ◽  
Quality Measures ◽  
Facet Classification

FRI0524 THE ACR’S RHEUMATOLOGY INFORMATICS SYSTEM FOR EFFECTIVENESS (RISE) REGISTRY SUPPORTS SMALL RHEUMATOLOGY PRACTICES FOR FEDERAL QUALITY REPORTING PROGRAM

2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 861-862
Author(s):  
Z. Izadi ◽  
T. Johansson ◽  
J. LI ◽  
G. Schmajuk ◽  
J. Yazdany
Keyword(s):  
Quality Measures ◽  
Quality Reporting ◽  
Practice Characteristics ◽  
Informatics System ◽  
Group Practices ◽  
Status Assessment ◽  
And Performance ◽  
Reporting Programs

Background:The Rheumatology Informatics System for Effectiveness (RISE) Registry was developed by the ACR to help rheumatologists improve quality of care and meet federal reporting requirements. In the current quality program administered by the U.S. Centers for Medicare and Medicaid services, rheumatologists are scored on quality measures, and performance is tied to financial incentives or penalties. Rheumatoid arthritis (RA)-specific quality measures can only be submitted through RISE to federal programs.Objectives:This study used data from the RISE registry to investigate rheumatologists’ federal reporting patterns on five RA-specific quality measures in 2018 and investigated the effect of practice characteristics on federal reporting of these measures.Methods:We analyzed data on all rheumatologists who continuously participated in RISE between Jan 2017 to Dec 2018 and who had patients eligible for at least one RA-specific measure. Five measures were examined: tuberculosis screening before biologic use, disease activity assessment, functional status assessment, assessment and classification of disease prognosis, and glucocorticoid management. We assessed whether or not rheumatologists reported specific quality measures via RISE. We investigated the effect of practice characteristics (practice structure; number of providers; geographic region) on the likelihood of reporting using adjusted analyses that controlled for measure performance (performance in 2018; change in performance from 2017; and performance relative to national average performance). Analyses accounted for clustering by practice.Results:Data from 799 providers from 207 practices managing 213,757 RA patients was examined. The most common practice structure was a single-specialty group practice (53%), followed by solo (28%) and multi-specialty group practice (12%). Most providers (73%) had patients eligible for all five RA quality measures. Federal reporting of quality measures through RISE varied significantly by provider, ranging from no reporting (60%) to reporting all eligible RA measures (12.2%). Reporting through RISE also varied significantly by quality measure and was highest for functional status assessment (36%) and lowest for assessment and classification of disease prognosis (20%). Small practices (1-4 providers) were more likely to report all eligible RA quality measures compared to larger practices (21%, 6%; p<0.001). In adjusted analyses, solo practices were more likely than single-specialty group practices to report RA measures (42%, 31%; p<0.027) while multispecialty group practices were less likely (18%, 31%; p<0.001). Additionally, higher performance in 2018 and performance ≥ the national average performance was associated with federal reporting of the measures through RISE (p≤0.004).Conclusion:Forty percent of U.S. rheumatologists participating in RISE used the registry for federal quality reporting. Physicians using RISE for reporting were disproportionately in small and solo practices, suggesting that the registry is fulfilling an important role in helping these practices participate in national quality reporting programs. Supporting small practices is especially important given the workforce shortages in rheumatology. We observed that practices reporting through RISE had higher measure performance than other participating practices, which suggests that the registry is facilitating quality improvement. Studies are ongoing to further investigate the impact of federal quality reporting programs and RISE participation on the quality of rheumatologic care in the United States.Disclaimer: This data was supported by the ACR’s RISE Registry. However, the views expressed represent those of the authors, not necessarily those of the ACR.Disclosure of Interests:Zara Izadi: None declared, Tracy Johansson: None declared, Jing Li: None declared, Gabriela Schmajuk Grant/research support from: Pfizer, Jinoos Yazdany Grant/research support from: Pfizer

Acoustic classification of coronal stops of Eastern Punjabi

Phonetica ◽  
2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Qandeel Hussain ◽  
Alexei Kochetov
Keyword(s):  
Standard Deviation ◽  
Voice Onset Time ◽  
Voice Quality ◽  
Onset Time ◽  
Quality Measures ◽  
Spectral Measures ◽  
Cepstral Peak Prominence ◽  
Laryngeal Configurations ◽  
Acoustic Classification

Abstract Punjabi is an Indo-Aryan language which contrasts a rich set of coronal stops at dental and retroflex places of articulation across three laryngeal configurations. Moreover, all these stops occur contrastively in various positions (word-initially, -medially, and -finally). The goal of this study is to investigate how various coronal place and laryngeal contrasts are distinguished acoustically both within and across word positions. A number of temporal and spectral correlates were examined in data from 13 speakers of Eastern Punjabi: Voice Onset Time, release and closure durations, fundamental frequency, F1-F3 formants, spectral center of gravity and standard deviation, H1*-H2*, and cepstral peak prominence. The findings indicated that higher formants and spectral measures were most important for the classification of place contrasts across word positions, whereas laryngeal contrasts were reliably distinguished by durational and voice quality measures. Word-medially and -finally, F2 and F3 of the preceding vowels played a key role in distinguishing the dental and retroflex stops, while spectral noise measures were more important word-initially. The findings of this study contribute to a better understanding of factors involved in the maintenance of typologically rare and phonetically complex sets of place and laryngeal contrasts in the coronal stops of Indo-Aryan languages.

scholarly journals Analysis of Developers’ Network and Change Burst Metrics as Predictors of Software Faults

2021 ◽  
Keyword(s):  
Software Quality ◽  
Software Metrics ◽  
Fault Prediction ◽  
Software Projects ◽  
Software Faults ◽  
Detection Probabilities ◽  
Software Quality Metrics ◽  
Network Metrics ◽  
Metrics Model

Introduction: Many software quality metrics that can be used as proxies of measuring software quality by predicting software faults have previously been proposed. However determining a superior predictor of software faults given a set of metrics is difficult since prediction performances of the proposed metrics have been evaluated in non–uniform experimental contexts. There is need for software metrics that can guarantee consistent superior fault prediction performances across different contexts. Such software metrics would enable software developers and users to establish software quality. Objectives: This research sought to determine a predictor for software faults that requires least effort to detect software faults and has least cost of misclassifying software components as faulty or not given developers’ network metrics and change burst metrics. Methods: Experimental data for this study was derived from Jmeter, Gedit, POI and Gimp open source software projects. Logistic regression was used to predict faultiness of a file while linear regression was used to predict number of faults per file. Results: Change burst metrics model exhibited the highest fault detection probabilities with least cost of mis-classification of components as compared to the developers’ network model. Conclusion: The study found that change burst metrics could effectively predict software faults.

Method of Evaluating the Weights of Software Quality Measures and Indicators

2017 ◽  
Vol 2 (2) ◽  
pp. 16
Author(s):  
Tetiana Hovorushchenko
Keyword(s):  
Quality Assessment ◽  
Software Quality ◽  
Quality Measures ◽  
Quality Characteristics ◽  
Quality Metrics ◽  
Requirements Specification ◽  
Software Requirements ◽  
Software Requirements Specification ◽  
Software Quality Metrics ◽  
First Time

Nowadays the actual task is evaluating the mutual influences of the software quality characteristics and subcharacteristics by the measures and software quality metrics – by the indicators. The aim of this study is the development of the method of evaluating the weights of software quality measures and indicators. The first time developed method of evaluating the weights of the software quality measures and indicators differs from known methods that: considers the correlation of software quality subchcaracteristics by the measures and metrics by the indicators, calculates the weights of exactly measures and indicators, provides the conclusion about the presence of which measures and indicators in the software requirements specification (SRS) is necessary for the appropriate level of veracity of the software quality assessment. The weights of the software quality measures and indicators provide the sorting of all missing in the SRS measures and indicators in descending of their significance (in descending of their weights), i.e. the priority of their further addition in the SRS.

Software Quality Measures as Degree of Excellence

2017 ◽  
pp. 57-66
Keyword(s):  
Software Engineering ◽  
Software Quality ◽  
Quality Measures ◽  
Error Level ◽  
Rate Of Improvement

This chapter attempts to develop a system to predict rate of improvement of the software quality at a particular point of time with respect to the number of lines of code present in the software. Having calculated the error level (EL) and degree of excellence (DE) at two points in time, I can move forward towards the estimation of the rate of improvement of the software quality with respect to time. This parameter can be used to judge the amount of effort put into while developing software and can add a new dimension to the understanding of software quality in software engineering domain.

scholarly journals Software quality measures validation in the Czech Republic

2008 ◽  
Vol 53 (No. 2) ◽  
pp. 94-100
Author(s):  
J. Vaníček
Keyword(s):  
Czech Republic ◽  
Software Quality ◽  
International Research ◽  
Main Part ◽  
Life Sciences ◽  
Quality Measures ◽  
International Standards ◽  
Research Project ◽  
The Czech Republic ◽  
International Research Project

The paper concludes the research results performed on the Faculty of Economics and Management, Czech University of Life Sciences in Prague, concerning the utilization and validation of external and internal software quality measures (metrics). The aim of this research was the validation of measures (metrics) recommended in the ISO/IEC 9126-2 and 9126-3 technical reports, with the intention to incorporate selected measures to international standards. The research presents the serious deficiencies and users provisions concerning these measures and the necessity of a deep revision of the set of measures before the decision about incorporating these measures into the ISO/IEC 250xx standards series, developed within the SQuaRE international research project. The main part of this contribution was presented at the conference Agricultural Perspectives XV, organised by the Czech University of Life Sciences in Prague, September 20 to 21, 2006.

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