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Software Engineering

Software Engineering. Dr. Thomas E. Potok Adjunct Professor UT Research Staff Member ORNL. Agenda. Project Midterm dates Risks Risk management. Risk. A very popular notion, but little studied Low risk projects are easy Only the courageous are willing to take on high-risk project

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Software Engineering

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  1. Software Engineering Dr. Thomas E. Potok Adjunct Professor UT Research Staff Member ORNL T. E. Potok - University of Tennessee

  2. Agenda • Project • Midterm dates • Risks • Risk management T. E. Potok - University of Tennessee

  3. Risk • A very popular notion, but little studied • Low risk projects are easy • Only the courageous are willing to take on high-risk project • You aren’t really doing your job if you don’t take on some risk T. E. Potok - University of Tennessee

  4. What is risk • Risks within a nuclear power plant • Meltdown • Radiation leak • Loss of power • Safety violation T. E. Potok - University of Tennessee

  5. Two components of risk • Potential loss or impact • What is the impact of a potential risk • If it happens, what is the result • Catastrophic - substantial loss of life, money, or property • Major - Significant injury, loss of money, or property • Minor - Mild injury, loss of money, or property • Trivial - Minimal injury, loss of money, or property T. E. Potok - University of Tennessee

  6. Two components of risk • Probability of occurrence • What is the probability that the risk will occur • How likely is it that the risk will occur • Quite likely - will occur • Likely - Probably will occur • Unlikely - Probably will not occur • Rare - Very unlikely T. E. Potok - University of Tennessee

  7. Impact Vs Probability High Probability and High Impact T. E. Potok - University of Tennessee

  8. Impact Vs. Probability • Nuclear meltdown is so rare (well almost) that even a catastrophic impact is acceptable • Likewise, a very probable even, such as a safety violation will have such a minor impact that it too is acceptable • Problems arises when a major problem is likely to occur T. E. Potok - University of Tennessee

  9. What to do with risks? • Reduce or avoid the impact of the risk • Put nuclear plants in low populated areas • Build plants with strong containment walls • Reduce or avoid the probability of the risk occurring • Install failsafe systems to prevent a meltdown • Train personnel on how to react in emergency situations T. E. Potok - University of Tennessee

  10. Software Risks Management • Objective: Identify, address, and eliminate software risks before they become a threat to the successful software operation • Actions • Risk Assessment • Risk identification • Risk Analysis • Risk Prioritization • Risk Control • Risk management planning • Risk resolution • Risk monitoring T. E. Potok - University of Tennessee

  11. Risk Identification • Checklists • Resource • Right people • Right equipment • Enough money • Schedules • Driven by economy • Driven by politics • Technology • Available • Maturity level • Requirements • Stability • Complexity T. E. Potok - University of Tennessee

  12. Resources • Wrong skills or experience • If you need Java code written, and no one knows Java, you are in trouble • Wrong leader • Leader is a great programmers, but does not know how to manage a project • Team conflicts • Two or more members compete more than collaborate • Team dynamics • A low output team should not be counted on for a high risk, complex project T. E. Potok - University of Tennessee

  13. Schedules • Schedules can be set by a variety of factors • Y2K fixes needs to be finished by Dec 31, 1999 • Political considerations - A politician want the software to work before an election • Economic considerations - Software sales can help the stockholder’s report • Technical - Software engineering estimates • Competition - Competitor drive the schedules • Because a schedule is set does not mean that it can be accomplished T. E. Potok - University of Tennessee

  14. Technology • Some technologies are mature and reasonable to implement • Databases • Basic applications • Searching and sorting • Some are not • NP complete problems • Semantic understanding • Reasoning/thinking T. E. Potok - University of Tennessee

  15. Requirements • Not known or clearly stated at the beginning of the project • The requirements shift or change during the project • Gold-plating - I am good at database, and every solution I offer has a database in it • Unspecified interfaces T. E. Potok - University of Tennessee

  16. Risk Analysis • Once risks have been identified, what do you do with them? • Analyze what risks you need to worry about • Plan based on analysis • But first, some background... T. E. Potok - University of Tennessee

  17. General Probability TheoryFrom M. A. Vouk • Basics • The probability of an event A occurring is between 0 and 1: • The probability of the entire sample space is 1 P(S) = 1 The probability of the union of two mutually exclusive events is the sum of their probabilities T. E. Potok - University of Tennessee

  18. Venn Diagrams A A Set A and its complement A B Mutually Exclusive Events T. E. Potok - University of Tennessee

  19. More diagrams S A B Intersection of events A and B T. E. Potok - University of Tennessee

  20. Probability of Two Events A and B are not mutually exclusive A and B are mutually exclusive T. E. Potok - University of Tennessee

  21. Example • The probability of working in the computer field is 60% • The probability of graduating with CS degree is 70% • The probability of either is 80%, the probability of BOTH is: • A = “finding a job in the computer field” • B = “student graduates in CS” = .6 + .7 - .8 = .5, or 50% T. E. Potok - University of Tennessee

  22. Example S = 20% AUB = 80% A = 60% B = 70% Intersection of events A and B = 50% T. E. Potok - University of Tennessee

  23. Conditional Events • The event A occurs under the condition that B has occurred • Example: You get a CS degree, Event B, what is your chance of finding a job in the field, Event A? • = .5/.7 = .71, or 71%, up from 60% T. E. Potok - University of Tennessee

  24. Independence • Two events are said to be independent iff the joint probability is 0. • Bayes’ Rule T. E. Potok - University of Tennessee

  25. Example • A - We need to increase disk space with ISP • B - We need the ISP to support video • Probability of A is 80%, B is 60%, and A and B are independent events • .8 x.6 = .48, or a 48% chance of both A and B occurring T. E. Potok - University of Tennessee

  26. Further Example • Four independent events must take place for the project to be successful • Software from vendor A, 90% • Hardware from vendor B, 80% • Design from vendor C, 90% • Successful code from vendor D, 70% • Looks like the project is in good shape • What is the probability of success? • .9*.8*.9*.7 = .45, less than 50% T. E. Potok - University of Tennessee

  27. Back to Risk • Expected loss from a risk can be defined as: • Probability of loss X loss if the event occurs • If you repeated this event many times, on average you would expect to loss this much • Provides a way of comparing risks • Provides a way of financially quantifying risk T. E. Potok - University of Tennessee

  28. Example • Project 1 • Estimated project cost: $500,000 • Estimated profit: $100,000 • Risk: Interfaces not understood • Loss $500,000 + money invested in the project • Assume $750,000 • Probability of risk: 30% • Expected loss of $225,000!! • Clearly this project is not worth the risk T. E. Potok - University of Tennessee

  29. However,... • If we can determine the interfaces • Work at AMI to test in interfaces (feasibility study) • Risk: Project not doable • Loss $500,000 + money invested in the project • Assume $550,000, ($50,000 for feasibility) • Probability of risk: 10%, we are confident it will work • Expected loss of $55,000 • Expected profit of $45,000. May be worth doing. T. E. Potok - University of Tennessee

  30. Decision Trees } $100,000 Easy .1 $-150,000 Hard .1 $0 Build Undoable .8 $-200,000 Check Writing Problem } Easy .5 $100,000 Experiment $72,500 $45,000 Hard .5 Reject } $-5000 $-5,000 T. E. Potok - University of Tennessee

  31. Risk Prioritization • Risks with the highest expected losses are usually the highest priority • Intangibles • Loss of prestige • Loss of a key customer • Loss of reputation T. E. Potok - University of Tennessee

  32. Risk list • Keep track of the top 10 risks on a project • Prioritize the list • based on expected loss • expert assessment • Develop action plans for each risk • Review the list on a regular basis T. E. Potok - University of Tennessee

  33. Risk Management Planning • For the highest priority risks • Identify ways of reducing probability of occurrence • Buy information • Inspect or monitor • Test T. E. Potok - University of Tennessee

  34. Buying Information • Spend money to understand the problem better • Research - what has been done in the past, what are others doing • Prototypes - develop a system to test risk probabilities • Buy COTS to solve the problem T. E. Potok - University of Tennessee

  35. Example • Reducing the risk of the interface problem • Spend some time researching foundation and quicken • Prototype solutions against each • Review the results with the customer • Look for commercial software packages that already does this • The more you spend, the more you understand the risks, and the less profit you make T. E. Potok - University of Tennessee

  36. Monitoring and Inspecting • To prevent unauthorized check writing • Establish a manual process of reviewing the audit logs • Incorporate two distinct methods for generating and analyzing the logs • Flag questionable transactions • Shut down the system until validation has been received T. E. Potok - University of Tennessee

  37. Testing • Establish a series of test scripts based on fraudulent transactions • Review the scripts with financial experts to ensure accuracy • Test the software so that it works fully with the script • Test manual procedures as well T. E. Potok - University of Tennessee

  38. Reducing the Potential Loss • Contingency plans • Plan what to do, if a problem does arise • Simple, but rarely done • Rework to reduce obvious risk • Keep things simple! T. E. Potok - University of Tennessee

  39. Example • Develop an audit trail • If not doable • Have the function be performed by the AMI accountant • Use the database or quicken logging function • Print a copy of each check written T. E. Potok - University of Tennessee

  40. Rework • Rework is typically viewed as a waste of time and resources • However, in high risk situations, rework may be necessary to reduce or eliminate risks • The iterative process involves a good deal of rework, but the project risks are usually found early. T. E. Potok - University of Tennessee

  41. Summary • Risks Analysis • Probability • Risk management • Risk reduction T. E. Potok - University of Tennessee

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