Master's ºÝºÝߣs
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slidepack used at the master's degree defense: probabilistic models for risk assessment in SQA
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Master's ºÝºÝߣs
- 1. PROBABILISTIC MODELS FOR RISKS ASSESSMENT IN SOFTWARE QUALITYASSURANCE §£§Ö§â§à§ñ§ä§ß§à§ã§ä§ß§í§Ö §Þ§à§Õ§Ö§Ý§Ú §Õ§Ý§ñ §à§è§Ö§ß§Ü§Ú §â§Ú§ã§Ü§à§Ó §ã§Ó§ñ§Ù§Ñ§ß§ß§í§ç §ã §à§Ò§Ö§ã§á§Ö§é§Ö§ß§Ú§Ö§Þ §Ü§Ñ§é§Ö§ã§ä§Ó§Ñ §±§°
- 2. 04.06.1996, Centre Spatial Guyanais , Kourou
- 3. 40 seconds after initiation of the flight sequence at an altitude of 3700 m the launcher veered off its flight path, broke up and exploded. Total loss US$370 million
- 4. ?
- 7. R (A) =P (A) ¡¤L (A) Risk is a potential undesired event which, if occurs, will cause loss. §²§Ú§ã§Ü ¨C §ï§ä§à §Ó§à§Ù§Þ§à§Ø§ß§à§Ö §ß§Ö§Ø§Ö§Ý§Ñ§ä§Ö§Ý§î§ß§à§Ö §ã§à§Ò§í§ä§Ú§Ö, §Ü§à§ä§à§â§à§Ö, §Ó §ã§Ý§å§é§Ñ§Ö, §Ö§ã§Ý§Ú §à§ß§à §á§â§à§Ú§Ù§à§Û§Õ§×§ä, §á§â§Ú§Ó§Ö§Õ§×§ä §Ü §á§à§ä§Ö§â§ñ§Þ.
- 8. R (A) = P (A) ¡¤ L (A) Risk is a potential undesired event which, if occurs, will cause loss. §²§Ú§ã§Ü ¨C §ï§ä§à §Ó§à§Ù§Þ§à§Ø§ß§à§Ö §ß§Ö§Ø§Ö§Ý§Ñ§ä§Ö§Ý§î§ß§à§Ö §ã§à§Ò§í§ä§Ú§Ö, §Ü§à§ä§à§â§à§Ö, §Ó §ã§Ý§å§é§Ñ§Ö, §Ö§ã§Ý§Ú §à§ß§à §á§â§à§Ú§Ù§à§Û§Õ§×§ä, §á§â§Ú§Ó§Ö§Õ§×§ä §Ü §á§à§ä§Ö§â§ñ§Þ.
- 9. R (A) = P (A) ¡¤L (A) Risk is a potential undesired event which, if occurs, will cause loss. §²§Ú§ã§Ü ¨C §ï§ä§à §Ó§à§Ù§Þ§à§Ø§ß§à§Ö §ß§Ö§Ø§Ö§Ý§Ñ§ä§Ö§Ý§î§ß§à§Ö §ã§à§Ò§í§ä§Ú§Ö, §Ü§à§ä§à§â§à§Ö, §Ó §ã§Ý§å§é§Ñ§Ö, §Ö§ã§Ý§Ú §à§ß§à §á§â§à§Ú§Ù§à§Û§Õ§×§ä, §á§â§Ú§Ó§Ö§Õ§×§ä §Ü §á§à§ä§Ö§â§ñ§Þ.
- 10. R (A) =P (A) ¡¤L (A) Risk is a potential undesired event which, if occurs, will cause loss. §²§Ú§ã§Ü ¨C §ï§ä§à §Ó§à§Ù§Þ§à§Ø§ß§à§Ö §ß§Ö§Ø§Ö§Ý§Ñ§ä§Ö§Ý§î§ß§à§Ö §ã§à§Ò§í§ä§Ú§Ö, §Ü§à§ä§à§â§à§Ö, §Ó §ã§Ý§å§é§Ñ§Ö, §Ö§ã§Ý§Ú §à§ß§à §á§â§à§Ú§Ù§à§Û§Õ§×§ä, §á§â§Ú§Ó§Ö§Õ§×§ä §Ü §á§à§ä§Ö§â§ñ§Þ.
- 11. QUALITY MODELS §®§°§¥§¦§§ª §¬§¡§¹§¦§³§´§£§¡ §±§°
- 12. QUALITY CRITERIA §¬§²§ª§´§¦§²§ª§ª §¬§¡§¹§¦§³§´§£§¡ §±§°
- 13. METHODOLOGY Phase1. Preparation for Risks Identification and Evaluation Phase2. Risks Identification, Initial Evaluation and Assignment Session Phase3. Risks Analysis and Actualisation Phase4. Defining Prevention and Mitigation Measures, establishing regular reviews. §±§à§Õ§Ô§à§ä§à§Ó§Ú§ä§Ö§Ý§î§ß§Ñ§ñ §æ§Ñ§Ù§Ñ §Ü §Ó§í§ñ§Ó§Ý§Ö§ß§Ú§ð §Ú §à§è§Ö§ß§Ü§Ö §â§Ú§ã§Ü§à§Ó. §¶§Ñ§Ù§Ñ-§ã§Ö§ã§ã§Ú§ñ §Õ§Ý§ñ §à§Ò§ß§Ñ§â§å§Ø§Ö§ß§Ú§ñ, §ß§Ñ§é§Ñ§Ý§î§ß§à§Û §à§è§Ö§ß§Ü§Ú §Ú §â§Ñ§ã§á§â§Ö§Õ§Ö§Ý§Ö§ß§Ú§ñ §à§ä§Ó§Ö§ä§ã§ä§Ó§Ö§ß§ß§à§ã§ä§Ú §Ù§Ñ §Ñ§ß§Ñ§Ý§Ú§Ù §â§Ú§ã§Ü§à§Ó §¡§ß§Ñ§Ý§Ú§Ù §Ú §Ñ§Ü§ä§å§Ñ§Ý§Ú§Ù§Ñ§è§Ú§ñ §â§Ú§ã§Ü§à§Ó §°§á§â§Ö§Õ§Ö§Ý§Ö§ß§Ú§Ö §á§â§Ö§Ó§Ö§ß§ä§Ú§Ó§ß§í§ç §Ú §ã§Þ§ñ§Ô§é§Ñ§ð§ë§Ú§ç §Þ§Ö§â. §³§à§Ô§Ý§Ñ§ê§Ö§ß§Ú§Ö §à §â§Ö§Ô§å§Ý§ñ§â§ß§í§ç §á§Ö§â§Ö§ã§Þ§à§ä§â§Ñ§ç .
- 14. Preliminary Risk or Hazard Analysis Hazard and Operability Study Failure Mode and Effects Analysis Fault Tree Analysis Event Tree Analysis Cause-Consequence Analysis GO Method Fault Graph Method Markov Modelling Dynamic Event Logic Analytical Methodology Dynamic Event Tree Analysis Method Bow Tie Risk Matrices Data Domain Models Input-domain models Fault-seeding models Mill's Error Seeding Model Homogeneous Markov Models Non-Homogeneous Markov Models Semi-Markov Models Jelinski-Moranda Failure Rate Model Littlewood-Veraal Bayesian SRG model Musa¡¯s Model Krishnamurthy-Mathur¡¯s Model RISK ANALYSIS §¡§¯§¡§§ª§© §²§ª§³§¬§°§£
- 15. §±§à §ã§å§ë§Ö§ã§ä§Ó§å, §Ó§ã§Ö §Þ§à§Õ§Ö§Ý§Ú §à§ê§Ú§Ò§à§é§ß§í, §ß§à §ß§Ö§Ü§à§ä§à§â§í§Ö - §á§à§Ý§Ö§Ù§ß§í . Essentially, all models are wrong, but some are useful Box, George E. P.; Norman R. Draper (1987). Empirical Model-Building and Response Surfaces.
- 16. §²§¦§©§µ§§¾§´§¡§´§½ §°§á§â§Ö§Õ§Ö§Ý§Ö§ß§í §á§à§ß§ñ§ä§Ú§ñ §â§Ú§ã§Ü§à§Ó §Ü§Ñ§é§Ö§ã§ä§Ó§Ñ §±§°, §à§á§Ú§ã§Ñ§ß§Ñ §Þ§Ö§ä§à§Õ§Ú§Ü§Ñ §Ó§í§ñ§Ó§Ý§Ö§ß§Ú§ñ §Ú §Þ§Ú§ß§Ú§Þ§Ú§Ù§Ñ§è§Ú§Ú §ã§ä§à§Ú§Þ§à§ã§ä§Ú §â§Ú§ã§Ü§à§Ó, §ã§Ó§ñ§Ù§Ñ§ß§ß§í§ç §ã §Ü§Ñ§é§Ö§ã§ä§Ó§à§Þ §±§° §°§á§Ú§ã§Ñ§ß§í §Ó§Ö§â§à§ñ§ä§ß§à§ã§ä§ß§í§Ö §Þ§à§Õ§Ö§Ý§Ú §Õ§Ý§ñ §à§è§Ö§ß§Ü§Ú §â§Ú§ã§Ü§à§Ó, §ã§Ó§ñ§Ù§Ñ§ß§ß§í§ç §ã §ß§Ñ§Õ§×§Ø§ß§à§ã§ä§î§ð §±§° §¥§Ñ§ß§í §â§Ö§Ü§à§Þ§Ö§ß§Õ§Ñ§è§Ú§Ú §á§à §Ú§ã§á§à§Ý§î§Ù§à§Ó§Ñ§ß§Ú§ð §Þ§Ö§ä§à§Õ§à§Ó §Ñ§ß§Ñ§Ý§Ú§Ù§Ñ §â§Ú§ã§Ü§à§Ó, §ã§Ó§ñ§Ù§Ñ§ß§ß§í§ç §ã §Ü§Ñ§é§Ö§ã§ä§Ó§à§Þ §±§°