About Spikes
A spike solution, or spike, is a technical investigation. It's a small experiment to research the answer to a problem. For example, a programmer might not know whether Java throws an exception on arithmetic overflow. A quick ten-minute spike will answer the question.
The Agile Fluency Project by James Shore — Kickstarter - 2 views
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Check out the Agile Fluency Project immersion experience for a taste of Agile Done Well http://t.co/vQeqIaehck #AgileFluencyProject
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Check out the Agile Fluency Project immersion experience for a taste of Agile Done Well http://t.co/vQeqIaehck #AgileFluencyProject
James Shore: The Art of Agile Development: Spike Solutions - 0 views
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Performing the Experiment The best way to implement a spike is usually to create a small program or test that demonstrates the feature in question. You can read as many books and tutorials as you like, but it's my experience that nothing helps me understand a problem more than writing working code. It's important to work from a practical point of view, not just a theoretical one.
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Writing code, however, often takes longer than reading a tutorial. Reduce that time by writing small, standalone programs.
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http://studios.thoughtworks.com/2007/5/10/continuous-integration-in-the-enterprise-with... - 0 views
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One of the developers had checked in some code that failed the regression tests. The application, on which the company had spent considerable time, money and effort, was now in an uncertain state. It wasn't behaving as expected. In the past, this type of bug usually wasn't discovered for months. Usually, it wasn't discovered until the System Integration Testing cycle got underway. For this project, that wasn't scheduled for another 6 months.
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In the past, this bug would have lingered in the code for 6 months before anyone even realized it was a problem
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. The light had gone off only 6 minutes after the code had been committed. Notice: not 6 months...but 6 minutes!
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Kanban development oversimplified: a simple explanation of how Kanban adds to the ever-... - 0 views
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It’s a lot easier to estimate a story that’s small — which can lead to more accurate estimates, and better predictability.
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It’s easier to plan with smaller stories. With big stories — stories that might take weeks for a developer to implement — it becomes difficult to plan a development time-box — particularly when the iterations are only a couple of weeks. It seems that only a couple stories fit — and there’s often room for half a story — but how do you build half a story? Splitting them into smaller stories makes it easier to plan those time-boxes.
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Shrinking stories forces earlier elaboration and decision-making. Where product owners could write their stories fairly generally and consider many of the details later, now breaking them down into smaller stories forces more thinking earlier in a planning lifecycle.
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InfoQ: Comparing Kanban To Scrum - 1 views
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Scrum in a nutshell Split your organization into small, cross-functional, self-organizing teams. Split your work into a list of small, concrete deliverables. Assign someone to be responsible for that list and to sort the list by priority. The implementation team estimates the relative size of each item. Split time into short fixed-length iterations (usually 1 – 4 weeks), with potentially shippable code demonstrated after each iteration. Optimize the release plan and update priorities in collaboration with the customer, based on insights gained by inspecting the release after each iteration. Optimize the process by having a retrospective after each iteration. For more details check out “Scrum and XP from the Trenches”. The book is a free read online. I know the author, he’s a nice guy :o) http://www.crisp.se/ScrumAndXpFromTheTrenches.html Kanban in a nutshell Visualize the workflow Split the work into pieces, write each item on a card and put on the wall Use named columns to illustrate where each item is in the workflow Limit WIP (work in progress) – assign explicit limits to how many items may be in progress at each workflow state. Measure the lead time (average time to complete one item, sometimes called “cycle time”), optimize the process to make lead time as small and predictable as possible.
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