1. Course summary TDT4235 Tor Stålhane IDI / NTNU

2. What we try to do QA – Create trust to a product or service SPI – Solve fuzzy problems by –Identifying and describing the problem –Collect information to understand the problem –Select a potentially useful technique –Arrive at a useable solution

3. Create trust Product Tools and methods Trust Domain knowledge

4. A “soft” problem Problem Available tools and methods Possible solution Experience Method 4 Method … Method 2 Method … Method 7 Method 3 Method n Method 6 Method 1 Method 5

5. Summary of Quality Assurance – 1 QA is about two things: Having a way of working that is – Defined – there is clear description – Documented, written down for everybody to see – Communicated, everybody in the company knows about it – Agreed-upon, everybody in the company works this way Keeping our promises. When we have promised to do the job in a certain way, this is how it will be done if nothing else is agreed upon later.

6. Summary of Quality Assurance – 2 The QA department or the QA responsible needs to Check that we keep our promises Look for improvement opportunities – New things to do – Things to change – Things we should stop doing

7. Summary of Quality Assurance – 3 Quality control is not software process improvement a way to keep status quo.

8. Summary of SPI – 1 This part of the summary will focus on the SPI part of the course. The main messages are: SPI => change Change => risk Risk can be reduced or controlled by – Collecting data – Analysing data

9. Summary of SPI – 2

10. Summary of SPI – 3 The amount and type of data that we need to collect will depend on our Willingness to accept risk Time frame – when do we need it Planning horizon

11. The trade-off diagram Experience Data Risk 100%

12. Risk management – 1 “Risk management is project management for grown-ups” Needs to identify Risks – what can go wrong? – Frequency or probability – Consequences – Mitigation – what can we do about it?

13. Risk management – 2 Need to consider both risk, benefits and opportunities. Only benefits => too optimistic Only risks => too pessimistic Not opportunities => will not be able to grab them when and if they arise

14. Risk management – 2 Need to consider both risk, benefits and opportunities. Only benefits => too optimistic Only risks => too pessimistic Not opportunities => will not be able to grab them when and if they arise

15. L MH L L M M H H Probability Costs Benefits BEDCCA A, C are opportunities B is a benefit D is a cost C, E are risks The total view

16. The complete picture L MH L L M M H H Probability Costs Benefits BEDCCA A, C are opportunities B is a benefit D is a cost C, E are risks This will not happen by itself – it must be planned for. We must identify risk mitigations and opportunity enablers. Otherwise, we should just skip the whole thing

17. How much risk are we willing to take

18. The data collection process As shown in the next diagram, we will keep on collecting data until we Can reduce the decision risks to an acceptable level Run out of time or money

19. Collect info Perform risk Final SPI plan More time available Yes Plan SPI activities assessment Acceptable risk Yes No

20. Data collection Data analysis Improvement opportunities Improvement activity Improvement implementation Company priorities Qualitative Quantitative

21. Data collection Data analysis Qualitative Quantitative Affinity diagrams Interviews Questionnaires Gap analysis SWOT Data archaeology GQM Error reports Surveys Data archaeology Data plots RCA – trees and networks Force fields Statistics

22. PDCA and risk The amount of risk we are willing to accept and the corresponding actions or lack thereof can be illustrated by using different versions of the PDCA cycle.

23. Plan Do Check Act NeedsImprovements SWOT / SWIR Gap analysis Planning Risk assessment Delphi analysis Data archeology KJ / affinity diagrams Pilot projects GQM Plotting techniques Statistical analyses Root Cause Analysis Risk assessment Introduce changes What are the results Post Mortem Analysis

24. Plan Do Check Act NeedsImprovements SWOT / SWIR Data archeology Delphi analysis Root Cause Analysis Risk assessment Introduce changes What are the results

25. Plan Do Check Act NeedsImprovements Planning GQM Pilot project Plotting techniques Statistical analyses Root Cause Analysis Risk assessment Introduce changes What are the results

26. Plan Do Check Act NeedsImprovements Gap analysis KJ / affinity diagrams Root Cause Analysis Risk assessment Introduce changes What are the results

27. Plan Do Check Act NeedsImprovements Post Mortem Analysis Risk assessment Introduce changes What are the results Gap analysis Risk assessment

28. ProcessProjectMeasurementAnalysis Relevant data Historical data ExperienceKnowledge PMA Improvement opportunities

29. ProcessProjectMeasurementAnalysis Relevant data Historical data ExperienceKnowledge GQM Improvement opportunities

30. ProcessProjectMeasurementAnalysis Relevant data Historical data ExperienceKnowledge Proactive SPI or Only subjective data – e.g. Delphi Improvement opportunities

31. What is the status? e.g. SWOT Management decidesSelect area Action Results Collect data Analyze data ActionResults

32. The trade-off diagram Experience Data 100% We would like to be here Risk We will often have to be here

33. Last – but not least There is a clear tendency for the software industry to move towards more fast, small projects SPI and QA will have to follow or run the risk of being irrelevant.