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Empirical estimates of software availability of deployed systems

Published: 21 September 2006 Publication History

Abstract

We consider empirical evaluation of the availability of the deployed software. Evaluation of real systems is more realistic, more accurate, and provides higher level of confidence than simulations, testing, or models. We process and model information gathered from a variety of operational and service support systems to obtain estimates of software reliability and availability. The three principal quantities are the total runtime, the number of outages, and the duration of outages. We consider methods to assess the quality of information in customer support systems, discuss advantages and disadvantages of various sources, consider methods to deal with missing data, and ways to construct bounds on measures that are not directly available. We propose a method to assess empirically software availability and reliability based on information from operational customer support and inventory systems and use a case study of a large communications system to investigate factors affecting software reliability. We find large variations among platforms and releases and find the failure rate to vary over time.

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  • (2011)Source code survival with the Kaplan MeierProceedings of the 2011 27th IEEE International Conference on Software Maintenance10.1109/ICSM.2011.6080823(524-527)Online publication date: 25-Sep-2011
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cover image ACM Conferences
ISESE '06: Proceedings of the 2006 ACM/IEEE international symposium on Empirical software engineering
September 2006
388 pages
ISBN:1595932186
DOI:10.1145/1159733
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 21 September 2006

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Cited By

View all
  • (2019)Search of Software Artefacts Based on the Project Quantitative CharacteristicsProceedings of the 2019 2nd International Conference on Geoinformatics and Data Analysis10.1145/3318236.3318252(26-30)Online publication date: 15-Mar-2019
  • (2014)An Investigation of Object-Oriented and Code-Size Metrics as Dead Code PredictorsProceedings of the 2014 40th EUROMICRO Conference on Software Engineering and Advanced Applications10.1109/SEAA.2014.67(392-397)Online publication date: 27-Aug-2014
  • (2011)Source code survival with the Kaplan MeierProceedings of the 2011 27th IEEE International Conference on Software Maintenance10.1109/ICSM.2011.6080823(524-527)Online publication date: 25-Sep-2011
  • (2011)Predicting post-release defects using pre-release field testing resultsProceedings of the 2011 27th IEEE International Conference on Software Maintenance10.1109/ICSM.2011.6080792(253-262)Online publication date: 25-Sep-2011
  • (2010)An Industrial Case Study on Speeding Up User Acceptance Testing by Mining Execution LogsProceedings of the 2010 Fourth International Conference on Secure Software Integration and Reliability Improvement10.1109/SSIRI.2010.15(131-140)Online publication date: 9-Jun-2010
  • (2006)Software support tools and experimental workProceedings of the 2006 international conference on Empirical software engineering issues: critical assessment and future directions10.5555/1767399.1767435(91-99)Online publication date: 26-Jun-2006

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