WO2003005248A3 - Using a bayesian belief network - Google Patents

Using a bayesian belief network Download PDF

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Publication number
WO2003005248A3
WO2003005248A3 PCT/EP2002/006065 EP0206065W WO03005248A3 WO 2003005248 A3 WO2003005248 A3 WO 2003005248A3 EP 0206065 W EP0206065 W EP 0206065W WO 03005248 A3 WO03005248 A3 WO 03005248A3
Authority
WO
WIPO (PCT)
Prior art keywords
bbn
events
sequence
dag
msc
Prior art date
Application number
PCT/EP2002/006065
Other languages
French (fr)
Other versions
WO2003005248A2 (en
Inventor
Jean-Jacques Gras
Original Assignee
Motorola Inc
Jean-Jacques Gras
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Motorola Inc, Jean-Jacques Gras filed Critical Motorola Inc
Priority to AU2002302638A priority Critical patent/AU2002302638A1/en
Publication of WO2003005248A2 publication Critical patent/WO2003005248A2/en
Publication of WO2003005248A3 publication Critical patent/WO2003005248A3/en

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Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/36—Preventing errors by testing or debugging software
    • G06F11/3604—Software analysis for verifying properties of programs
    • G06F11/3608—Software analysis for verifying properties of programs using formal methods, e.g. model checking, abstract interpretation

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Software Systems (AREA)
  • Computer Hardware Design (AREA)
  • Quality & Reliability (AREA)
  • Physics & Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Debugging And Monitoring (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)
  • Stored Programmes (AREA)

Abstract

A method of determining probabilities associated with a sequence of events in a system, for example an item of software or a software system being developed. A scenario, e.g. a message sequence chart, MSC (1,51), is parsed into a directed acyclic graph, DAG (21), comprising nodes (22) and edges (24), by associating the edges to messages (8,10) and sequential relations between consecutive events in the MSC (1,51). A Bayesian belief network, BBN (31), is formed using the DAG (21). BBN conditional probability tables associated with each event are computed, and the overall probabilities associated with the sequence of events is determined from the BBN conditional probaility tables. This can be used for example to provide analysis of reliability early in a soft ware development cycle. Alternative applications, e.g. to project management, are possible.
PCT/EP2002/006065 2001-07-05 2002-06-03 Using a bayesian belief network WO2003005248A2 (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
AU2002302638A AU2002302638A1 (en) 2001-07-05 2002-06-03 Using a bayesian belief network

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
GB0116314.6 2001-07-05
GB0116314A GB2377513A (en) 2001-07-05 2001-07-05 Using a Bayesian Belief Network to model system reliability

Publications (2)

Publication Number Publication Date
WO2003005248A2 WO2003005248A2 (en) 2003-01-16
WO2003005248A3 true WO2003005248A3 (en) 2003-12-18

Family

ID=9917891

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/EP2002/006065 WO2003005248A2 (en) 2001-07-05 2002-06-03 Using a bayesian belief network

Country Status (3)

Country Link
AU (1) AU2002302638A1 (en)
GB (1) GB2377513A (en)
WO (1) WO2003005248A2 (en)

Families Citing this family (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20060112045A1 (en) 2004-10-05 2006-05-25 Talbot Patrick J Knowledge base comprising executable stories
WO2008029126A2 (en) 2006-09-07 2008-03-13 Bae Systems Plc Methods and apparatus for assisting with construction of data for use in an expert system
CN106570281B (en) * 2016-11-08 2020-04-17 上海无线电设备研究所 Bayesian reliability evaluation method for small subsample product based on similar product information
CN108664400B (en) * 2018-05-11 2020-08-04 北京航空航天大学 Construction method of fault diagnosis technology based on dependent Bayesian network
WO2020036559A2 (en) * 2018-06-05 2020-02-20 İzmi̇r Yüksek Teknoloji̇ Ensti̇tüsü Program slicing and bayesian network based method of determining functions to be changed in new version of software
CN110633524B (en) * 2019-09-12 2021-05-07 中国人民解放军军事科学院国防科技创新研究院 Reliability analysis method of complex polymorphic satellite system under non-independent probability condition
CN110688152B (en) * 2019-09-27 2021-01-01 厦门大学 Software reliability quantitative evaluation method combining software development quality information
CN110826237B (en) * 2019-11-11 2024-01-23 云南电网有限责任公司电力科学研究院 Wind power equipment reliability analysis method and device based on Bayesian belief network
CN111538654B (en) * 2020-04-09 2024-02-13 哈尔滨工业大学（威海） Software reliability test method, system and storage medium
CN112907140A (en) * 2021-03-29 2021-06-04 建信金融科技有限责任公司 Software project construction period evaluating method and device, electronic equipment and medium
CN116881675B (en) * 2023-09-07 2023-12-08 南京中鑫智电科技有限公司 Power equipment state monitoring method based on Bayesian algorithm

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6076083A (en) * 1995-08-20 2000-06-13 Baker; Michelle Diagnostic system utilizing a Bayesian network model having link weights updated experimentally
US6195594B1 (en) * 1997-11-25 2001-02-27 Voyan Technology Real-time planner for design
US6785636B1 (en) * 1999-05-14 2004-08-31 Siemens Corporate Research, Inc. Fault diagnosis in a complex system, such as a nuclear plant, using probabilistic reasoning
US6892317B1 (en) * 1999-12-16 2005-05-10 Xerox Corporation Systems and methods for failure prediction, diagnosis and remediation using data acquisition and feedback for a distributed electronic system

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
K. LASKEY ET AL.: "Development of Bayesian Networks from Unified Modeling Language Artifacts", 12TH INTERNATIONAL CONF ON SOFTWARE ENGINEERING AND KNOWLEDGE ENGINEERING, 6 August 2000 (2000-08-06), Chicago, IL, USA, XP002259619, Retrieved from the Internet <URL:http://ite.gmu.edu/~klaskey/papers/Laskey_Barry_BrouseUMLBayes.pdf> [retrieved on 20031029] *
V. CORTELLESSA ET AL.: "Deriving a Queueing Network based Performance Model from UML Diagrams", WOSP 2000, 17 September 2000 (2000-09-17), Ontario, Canada, pages 58 - 70, XP002259620, Retrieved from the Internet <URL:http://delivery.acm.org/10.1145/360000/350406/p58-cortellesa.pdf?key1=350406&key2=2843347601&coll=GUIDE&dl=ACM&CFID=13509646&CFTOKEN=79090992> [retrieved on 20031029] *

Also Published As

Publication number Publication date
AU2002302638A1 (en) 2003-01-21
GB0116314D0 (en) 2001-08-29
GB2377513A (en) 2003-01-15
WO2003005248A2 (en) 2003-01-16

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