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Software reliability: Additional investigations into modeling with replicated experiments
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Author and Affiliation:
Nagel, P. M.(Boeing Computer Services Co., Seattle, WA, United States)
Schotz, F. M.(Boeing Computer Services Co., Seattle, WA, United States)
Skirvan, J. A.(Boeing Computer Services Co., Seattle, WA, United States)
Abstract: The effects of programmer experience level, different program usage distributions, and programming languages are explored. All these factors affect performance, and some tentative relational hypotheses are presented. An analytic framework for replicated and non-replicated (traditional) software experiments is presented. A method of obtaining an upper bound on the error rate of the next error is proposed. The method was validated empirically by comparing forecasts with actual data. In all 14 cases the bound exceeded the observed parameter, albeit somewhat conservatively. Two other forecasting methods are proposed and compared to observed results. Although demonstrated relative to this framework that stages are neither independent nor exponentially distributed, empirical estimates show that the exponential assumption is nearly valid for all but the extreme tails of the distribution. Except for the dependence in the stage probabilities, Cox's model approximates to a degree what is being observed.
Publication Date: Jun 01, 1984
Document ID:
19840021433
(Acquired Nov 13, 1995)
Accession Number: 84N29502
Subject Category: COMPUTER PROGRAMMING AND SOFTWARE
Report/Patent Number: NASA-CR-172378, NAS 1.26:172378, BCS-40446
Document Type: Technical Report
Publisher Information: United States
Contract/Grant/Task Num: NAS1-16481
Financial Sponsor: NASA; United States
Organization Source: Boeing Computer Services Co.; Space and Military Applications Div.; Seattle, WA, United States
Description: 112p; In English
Distribution Limits: Unclassified; Publicly available; Unlimited
Rights: No Copyright
NASA Terms: DESIGN ANALYSIS; LIFE (DURABILITY); RELIABILITY ANALYSIS; SOFTWARE ENGINEERING; COMPUTER PROGRAMMING; ERROR ANALYSIS; MATHEMATICAL MODELS; MICROCOMPUTERS; PREDICTION ANALYSIS TECHNIQUES
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