Diese Präsentation wurde erfolgreich gemeldet.
Wir verwenden Ihre LinkedIn Profilangaben und Informationen zu Ihren Aktivitäten, um Anzeigen zu personalisieren und Ihnen relevantere Inhalte anzuzeigen. Sie können Ihre Anzeigeneinstellungen jederzeit ändern.

User stories: from good intentions to bad advice - Lean Agile Scotland 2019

351 Aufrufe

Veröffentlicht am

User stories are one of the most visible artefacts of most agile methods and, as such, have generated large quantities of expert advice. In my experience, much of that advice is open to misinterpretation.
In this session, we'll explore several classic pieces of advice, to see how misunderstandings can cause problems, despite the best intentions. The examples we'll look at are:
- an acronym: INVEST, created by Bill Wake
- a technique: relative estimation using story points, created by Ron Jeffries or Joseph Pelrine
- a template: Connextra (As-A/I-Want/So-That), created by Rachel Davies
Expert advice taken in good faith, that leads to bad outcomes, can cause us to become distrustful. It's time to reiterate that there is no magic formula, no silver bullet. At best, experts can lend you a framework within which to think, but their advice will never make thinking unnecessary.

Veröffentlicht in: Technologie
  • Loggen Sie sich ein, um Kommentare anzuzeigen.

User stories: from good intentions to bad advice - Lean Agile Scotland 2019

  1. 1. @sebrose http://smartbear.com Seb Rose User stories: from good intentions to bad advice
  2. 2. @sebrose http://smartbear.com Agenda Good intentions Examples: •Template •Acronym •Technique Bad outcomes Q & A
  3. 3. @sebrose http://smartbear.com “Experts” have good intentions
  4. 4. @sebrose http://smartbear.com “Experts” have good intentions Do we need experts?

  5. 5. @sebrose http://smartbear.com “Experts” have good intentions Do we need experts?
 Which experts do we trust?

  6. 6. @sebrose http://smartbear.com “Experts” have good intentions Do we need experts?
 Which experts do we trust?
 How do we want expertise delivered?
  7. 7. @sebrose http://smartbear.com As a <role> I want <goal/desire> So that <benefit> Template - Connextra
  8. 8. @sebrose http://smartbear.com Placeholder for a conversation
  9. 9. @sebrose http://smartbear.com Discussion
  10. 10. @sebrose http://smartbear.com Discussion What’s the connection between user stories and the Connextra template?
  11. 11. @sebrose http://smartbear.com Discussion What’s the connection between user stories and the Connextra template?
  12. 12. @sebrose http://smartbear.com Discussion What’s the connection between user stories and the Connextra template? What challenges have you experienced using the Connextra template?
  13. 13. @sebrose http://smartbear.com “That’s not a real user story …”
  14. 14. @sebrose http://smartbear.com “That’s not a real user story …” Too technical
  15. 15. @sebrose http://smartbear.com “That’s not a real user story …” Too technical Not shippable
  16. 16. @sebrose http://smartbear.com “That’s not a real user story …” Too technical Not shippable Wrong format
  17. 17. @sebrose http://smartbear.com Confetti party
  18. 18. @sebrose http://smartbear.com Confetti party
  19. 19. @sebrose http://smartbear.com Confetti party User stories are NOT requirements
  20. 20. @sebrose http://smartbear.com Confetti party User stories are NOT requirementsUser stories areEPHEMERAL
  21. 21. @sebrose http://smartbear.com This template has let us forget why user stories were invented
  22. 22. @sebrose http://smartbear.com Acronym
  23. 23. @sebrose http://smartbear.com Acronym
  24. 24. @sebrose http://smartbear.com I N V E S T Acronym
  25. 25. @sebrose http://smartbear.com Independent Negotiable Valuable Estimatable Small Testable I N V E S T Discussion
  26. 26. @sebrose http://smartbear.com Independent Negotiable Valuable Estimatable Small Testable I N V E S T Discussion
  27. 27. @sebrose http://smartbear.com Interpretation Independent Valuable and Let’s try to define
  28. 28. @sebrose http://smartbear.com IndependentI N V E S T
  29. 29. @sebrose http://smartbear.com Independent Dependent
  30. 30. @sebrose http://smartbear.com Valuable I N V E S T
  31. 31. @sebrose http://smartbear.com What is value?
  32. 32. @sebrose http://smartbear.com Minimum marketable feature (MMF)? What is value?
  33. 33. @sebrose http://smartbear.com Minimum marketable feature (MMF)? What is value? Potentially shippable increment?
  34. 34. @sebrose http://smartbear.com Minimum marketable feature (MMF)? What is value? Potentially shippable increment? Demonstrable functionality?
  35. 35. @sebrose http://smartbear.com Minimum marketable feature (MMF)? What is value? Potentially shippable increment? Demonstrable functionality? How might these interact with “Small”???
  36. 36. @sebrose http://smartbear.com Value is …
  37. 37. @sebrose http://smartbear.com anything that: Value is …
  38. 38. @sebrose http://smartbear.com anything that: Value is … - increases knowledge
  39. 39. @sebrose http://smartbear.com anything that: Value is … - increases knowledge - decreases risk
  40. 40. @sebrose http://smartbear.com anything that: Value is … - increases knowledge - decreases risk - generates useful feedback
  41. 41. @sebrose http://smartbear.com This acronym leaves plenty of room for misinterpretation
  42. 42. @sebrose http://smartbear.com Technique - story points
  43. 43. @sebrose http://smartbear.com - Have no units - Are relative - Are team specific - Estimated by people doing the work Story points - refresher
  44. 44. @sebrose http:// Story points are relative
  45. 45. @sebrose http://smartbear.com
  46. 46. @sebrose http://smartbear.com 120 cm 40 cm60 cm 100 cm 70 cm
  47. 47. @sebrose http://smartbear.com ... these studies which have for a few years now given rise to the claim that "research shows that people are better at relative than absolute estimation" do not in fact seem to square with that claim. http://guide.agilealliance.org/guide/relative.html
  48. 48. @sebrose http://smartbear.com ... these studies which have for a few years now given rise to the claim that "research shows that people are better at relative than absolute estimation" do not in fact seem to square with that claim. This doesn't entail that relative estimation doesn't work - only that it is not proven. http://guide.agilealliance.org/guide/relative.html
  49. 49. @sebrose http://smartbear.com
  50. 50. @sebrose http://smartbear.com 12 cm 4 cm 6 cm 10 cm 7 cm
  51. 51. @sebrose http:// Is it small, or just far away?
  52. 52. @sebrose http://smartbear.com This technique continues to cause massive dysfunction
  53. 53. @sebrose http://smartbear.comhttps://ronjeffries.com/articles/019-01ff/story-points/Index.html Story points - apology
  54. 54. @sebrose http://smartbear.com I certainly deplore their misuse; I think using them to predict “when we’ll be done” is at best a weak idea; I think tracking how actuals compare with estimates is at best wasteful; I think comparing teams on quality of estimates or velocity is harmful. Ron Jeffries https://ronjeffries.com/articles/019-01ff/story-points/Index.html Story points - apology
  55. 55. @sebrose http://smartbear.com https://estimation.lunarlogic.io/assets/cards-range-8fc41b2e3fd282125f4602a712020204.png https://estimation.lunarlogic.io/
  56. 56. @sebrose http://smartbear.com Bad outcomes
  57. 57. @sebrose http://smartbear.com Bad outcomes That doesn’t work here!
  58. 58. @sebrose http://smartbear.com No silver bullet Not only are there no silver bullets now in view, the very nature of software makes it unlikely that there will be any. Frederick P. Brooks "No Silver Bullet: Essence and Accidents of Software Engineering,"  Computer, Vol. 20, No. 4 (April 1987) pp. 10-19
  59. 59. @sebrose http://smartbear.com Examples revisited
  60. 60. @sebrose http://smartbear.com Examples revisited
  61. 61. @sebrose http://smartbear.com Examples revisited
  62. 62. @sebrose http://smartbear.com Examples revisited
  63. 63. @sebrose http://smartbear.com Patterns can help us filter •Name •Problem •Context •Forces •Solution •Resulting Context •Known Uses •Related Patterns •http://wiki.c2.com/?CanonicalForm
  64. 64. @sebrose http://smartbear.com Patterns can help us filter •Name •Problem •Context •Forces •Solution •Resulting Context •Known Uses •Related Patterns •http://wiki.c2.com/?CanonicalForm •Context •Forces
  65. 65. @sebrose http://smartbear.com Takeaways
  66. 66. @sebrose http://smartbear.com Takeaways Always consider your context
  67. 67. @sebrose http://smartbear.com Takeaways Concrete advice is often ambiguousAlways consider your context
  68. 68. @sebrose http://smartbear.com Takeaways Concrete advice is often ambiguousAlways consider your context Bad outcomes don’t mean the advice was bad
  69. 69. Seb Rose 
 Twitter: @sebrose Blog: http:/cucumber.io/blog E-mail: seb@smartbear.com http://bddbooks.com

×