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- W4288041570 abstract "Abstract Testing Non Functional Requirements (NFR) is critical for the success of software project. Among all NFR, software reliability testing is an ongoing challenge for software in general and safety critical systems in particular. Since software reliability, as a quality attribute, cannot be tested as a whole it therefore is decomposed in to sub factors e.g. availability, correctness, fault tolerance etc. each of which can be measured through set of metrics. One fundamental way to associate sub factors against metrics is through a conceptual framework. Existing frameworks in literature for software reliability testing have variation in sub factors and corresponding metrics through statistical evaluation. There is a need to identify and correlate sub factors and their corresponding metrics against software reliability testing. The association should be performed in a schematic way based upon empirical data gathered from target population i.e. reliability testers from global software industry. Since the conceptual framework is proposed to global software industry we therefore identified sub factors and their corresponding metrics from a sample of 81 global software reliability testing experts. All empirical data was evaluated through statistical analysis i.e. correlation and binary logistic regression. The data was also validated by a focus group of 11 experts who had up to 20 years of experience and had numerous certifications in the domain of reliability testing. A conceptual framework for reliability testing in which 33 metrics are correlated with maturity, 10 metrics are correlated with availability, 3 metrics are correlated with fault tolerance, 7 metrics are correlated with recoverability and 5 metrics are correlated with correctness are represented through a schematic relationship in hierarchical structure. A conceptual framework for reliability testing is designed which will not only facilitate in understanding of relationship between the sub factors and their corresponding metrics, it will also help in designing more effective test cases and their measurement through a set of relevant metrics. Statistical evaluation of sub factors and their corresponding metrics with reliability testing was evident through correlation analysis as their p-value < 0.05 and regression analysis since all sub factors and their corresponding metrics had positive coefficient." @default.
- W4288041570 created "2022-07-27" @default.
- W4288041570 creator A5042974412 @default.
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- W4288041570 date "2022-07-26" @default.
- W4288041570 modified "2023-09-27" @default.
- W4288041570 title "A Conceptual Framework for Software Reliability Testing" @default.
- W4288041570 doi "https://doi.org/10.21203/rs.3.rs-1725717/v1" @default.
- W4288041570 hasPublicationYear "2022" @default.
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