Although you may fear that developers don't have the requisite estimating skills, and this is often true at first, the fact is that it doesn't take long for people to get pretty good at estimating when they know that they're going to have to live up to those estimates. Smaller requirements are easier to estimate. User stories are a little larger but still relatively easy to estimate. Use cases , a staple of the Rational Unified Process RUP and the Agile Unified Process AUP , can become too large to estimate effectively although you can reorganize them into smaller and more manageable artifacts if you're flexible.
A good rule of thumb is that a requirement must be implementable within a single iteration. Scrum teams usually have month long iterations whereas XP teams often choose one or two weeks as an iteration length. Short iterations reduce the feedback cycle making it easier to stay on track.
Successful teams will deploy a working copy of their system at the end of each iteration into a demo environment where their potential stakeholders have access to it. This provides another opportunity for feedback, often generating new or improved requirements, and shows stakeholders that the team is making progress and thus their money is being invested wisely. This approach is desirable to IT professionals because it enables us to always be working on the highest-value functionality, as defined by our stakeholders, at all points in time.
This is not only a good business decision, it is also very satisfying for developers because they know that their work is actually having a positive impact on the organization. In short, with this sort of approach stakeholders are now in a position where they can govern their IT portfolio effectively. Figure 1 indicates that the items towards the top of the stack are described in greater detail than those towards the bottom. There's a few important things to understand: It's a significant risk to do detailed modeling up front.
The requirements in the current iteration must be understood in detail. You can't implement them properly if you don't understand them. This doesn't imply, however, that you need mounds of comprehensive documentation. You can model storm the details on a just in time JIT basis. You may decide model a bit ahead. For complex requirements which are approaching the top of the stack, you may choose to model them a few days or weeks in advance of implementing them so as to increase the speed of development.
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Note that any detailed modeling in advance of actually needing the information should be viewed as a risk because the priorities could change and you may never need that information. Many waterfall projects have failed when they have discovered, in an endless late-project "test-and-fix" phase, that the architecture is fatally flawed, or the components of the system cannot be integrated, or the features are entirely unusable, or the defects cannot possibly be corrected in time.
By practicing continuous testing in agile development, we more easily avoid both the risk that this will occur, and the constant dread of it. At both the unit level and acceptance feature level, we write the tests as the code itself is written beforehand. The most agile of agile development projects strive to automate as many tests as possible, relying on manual tests only when absolutely necessary. This speeds testing and delivers software that behaves predictably, which in turn gives us more continuous and more reliable feedback.
There is an emerging wealth of new tools, techniques, and best practices for rigorous continuous testing; much of the innovation is originating in the Test-Driven Development TDD community. When is a feature done? When all of its unit tests and acceptance tests pass, and the customer accepts it.
This is exactly what defines a running, tested feature. There is no better source of meaningful, highly-visible project metrics. We continuously refine both the system and the project. By reflecting on what we have done using both hard metrics like running, tested features and more subjective measures, we can then adjust our estimates and plans accordingly. But we also use the same mechanism to successively refine and continuously improve the process itself.
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Especially at the close of major milestones iterations, releases, etc. We look for points of leverage from which to shift those problems. We adjust the factory's machines, and acquire or invent new ones, to keep doing it a little better each release. We keep finding ways to adapt the process to keep delivering a little more value per unit time to the customer, the team, and the organization.
We keep maturing and evolving, like any healthy organism. Smaller agile development teams have been proven to be much more productive than larger teams, with the ideal ranging from five to ten people. If you have to scale a project up to more people, make every effort to keep individual teams as small as possible and coordinate efforts across the teams. Scrum-based organizations of up to have successfully employed a "Scrum of Scrums" approach to project planning and coordination.
With increments of production-ready software being delivered every iteration, teams must also be cross-functional in order to be successful. This means that an agile development team needs to include members with all of the skills necessary to successfully deliver software, including analysis, design, coding, testing, writing, user interface design, planning, and management. We need this because, again, each iteration is its own mini-project.
Teams work together to determine how best to take advantage of one another's skills and mentor each other. Teams transition away from designated testers and coders and designers to integrated teams in which each member helps do whatever needs doing to get the iteration done. Individual team members derive less personal identity from being a competitive expert with a narrow focus, and increasingly derive identity and satisfaction from being part of an extraordinarily productive and efficient team. As the positive reinforcement accumulates from iteration to iteration, the team becomes more cohesive.
Ambient levels of trust, camaraderie, empathy, collaboration, and job satisfaction increase.
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Software development becomes fun again. These outcomes are not guaranteed, but they are much likelier in well-managed agile development projects than elsewhere. Agility is a spectrum. Some teams are more agile than others, which are in turn more agile than yet others Agile Development Releases and Fixed-Length Iterations Agile software development methods have two main units of delivery: releases and iterations.
The result of each iteration is working, tested, accepted software and associated work items. Agile Development Delivers-Working, Tested Software Delivering working, tested features are an agile development team's primary measure of progress. Value-Driven Development Agile development methods focus rigorously on delivering business value early and continuously, as measured by running, tested software. Continuous Adaptive Planning It is a myth that agile methods forbid up-front planning. Multi-Level Planning in Agile Development Continuous planning is much more accurate if it occurs on at least two levels: At the release level, we identify and prioritize the features we must have, would like to have, and can do without by the deadline.
At the iteration level, we pick and plan for the next batch of features to implement, in priority order.
If features are too large to be estimated or delivered within a single iteration, we break them down further. Relative Estimation Many agile development teams use the practice of relative estimation for features to accelerate planning and remove unnecessary complexity. Examples include: days 1, 2, or 3 story points 4, 8, 16, 40, or 80 hours With relative estimation, estimating categories are approximate multiples of one another.
Emergent Feature Discovery As opposed to spending weeks or months detailing requirements before initiating development, agile development projects quickly prioritize and estimate features, and then refine details when necessary. Continuous Testing With continuous testing we deterministically measure progress and prevent defects. Continuous Improvement We continuously refine both the system and the project. Small, Cross-functional Teams Smaller agile development teams have been proven to be much more productive than larger teams, with the ideal ranging from five to ten people.
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