Test-driven development (TDD) is a common agile programming technique which has both specification and validation aspects. With TDD, you specify your software in detail on a just-in-time (JIT) basis via executable tests that are run in a regression manner to confirm that the system works to your current understanding of what your stakeholders require.
TDD is the combination of test-first development (TFD) and refactoring. With TFD, you write a single test (at either the requirements level with customer/acceptance tests or the design level with developer tests) and then you write just enough software to fulfill that test. Refactoring is a technique where you make a small change to your existing code to improve its design without changing its semantics.
TDD offers several benefits:1. It enables you to take small, safe steps during development, increasing programmer productivity.2. It increases quality. Agile developers are doing more testing, and doing it more often, than ever before. We're also fixing the problems that we find right on the spot.3. It helps to push validation activities early in the lifecycle, decreasing the average cost to fix defects (which rises exponentially the longer it takes you to detect them).4. Through single sourcing information, by treating tests as both specifications and as tests, we reduce the work required, increasing productivity.5. We leave behind valuable, up-to-date, detailed specifications for the people who come after us. Have you ever met a maintenance programmer who wouldn't want a full regression test suite for the code that they're working with?
But TDD isn't perfect. Although TDD is great at specifying code at a fine-grain level, tests simply don't scale to address higher level business process and architectural issues. Agile Model Driven Development (AMDD) enables you to scale TDD through initial envisioning of the requirements and architecture as well as just-in-time (JIT) modeling at the beginning and during construction iterations. To scale requirements-level TDD, you must recognize that customer tests are very good at specifying the details, but not so good at providing overall context. High-level business process models, conceptual domain models, and use cases are good at doing so, and these work products are often created as part of your initial requirements envisioning and iteration modeling activities. Similarly, to scale design-level TDD you must recognize that developer tests are very finely grained but once again do not provide overall context. High-level architecture sketches created during envisioning activities help set your initial technical direction. During each construction iteration, you'll do more detailed design modeling to think through critical issues before you implement them via TDD.
You also need to scale the validation aspects of TDD. TDD is in effect an approach to confirmatory testing where you validate the system to the level of your understanding of the requirements. The fundamental challenge with confirmatory testing, and hence TDD, is that it assumes that stakeholders actually know and can describe their requirements. Therefore you need to add investigative testing practices which explore issues that your stakeholders may not have thought of, such as usability issues, system integration issues, production performance issues, security issues, and a multitude of others.
For further reading, I suggest:1. My article "Introduction to TFD/TDD" at http://www.agiledata.org/essays/tdd.html which overviews TDD.2. My February 2008 column in Dr. Dobb's Journal entitled "Scaling TDD" at http://www.ddj.com/architect/205207998 which explores this issue in detail. 3. Andrew Glover's article "In pursuit of code quality: Adventures in behavior-driven development" at http://www.ibm.com/developerworks/java/library/j-cq09187/ which describes a new-and-improved take on TDD called BDD.[Read More]
Agility@Scale: Strategies for Scaling Agile Software Development
From archive: January 2008 X
ScottAmbler 120000HESD Tags:  tdd requirements design specification agileadopt agility-at-scale amdd testing 3 Comments 11,681 Views
During 2007 Per Kroll and myself invested a significant amount of time development a framework for lean development governance. This effort resulted in a series of three articles that were published in Rational Edge and a recently published white paper. The articles go into the various practices in detail whereas the paper provides an overview aimed at executives. I also recently did a webcast which is now available online. The URLs are at the bottom of this blog posting.
Development governance isn’t a sexy topic, but it critical to the success of any IT department. I like to compare traditional, command-and-control approaches to governance to herding cats – you do a bunch of busy work which seems like a great idea in theory, but in the end the cats will ignore your efforts and stay in the room. Yet getting cats out of a room is easy to accomplish, as long as you know what motivates cats. Simply wave some fish in front of their noses and you’ll find that you can lead them out of the room with no effort at all. Effective governance for lean development isn’t about command and control. Instead, the focus is on enabling the right behaviors and practices through collaborative and supportive techniques. It is far more effective to motivate people to do the right thing than it is to try to force them to do so.
This framework is based on the philosophical foundation provided by the 7 principles proposed in the book “Lean Software Development” by Mary and Tom Poppendieck. The 7 principles are:1. Eliminate Waste. The three biggest sources of waste in software development are the addition of extra features, churn, and crossing organizational boundaries. Crossing organizational boundaries can increase costs by 25% or more because they create buffers which slow down response time and interfere with communication. It is critical that development teams are allowed to organize themselves, and run themselves, in a manner which reflects the work that they’re trying to accomplish. 2. Build Quality In. If you routinely find problems with your verification process then your process must be defective. When it comes to governance, if you regularly find that developers are doing things that you don’t want them to do or are not doing things that they should be then your approach to governance must be at fault. The strategy is not to make governance yet another set of activities that you layer on top of your software process but instead should embed into your process to make it as easy as possible for developers to do the right thing. 3. Create Knowledge. Planning is useful, but learning is essential. 4. Defer Commitment. You do not need to start software development by defining a complete specification, but instead work iteratively. You can support the business effectively through flexible architectures that are change tolerant and by scheduling irreversible decisions to the last possible moment. This also requires the ability to closely couple end-to-end business scenarios to capabilities developed in potentially several different applications by different projects. 5. Deliver Fast. It is possible to deliver high-quality systems fast and in a timely manner. By limiting the work of a team to their capacity, by not trying to force them to do more than they are capable but instead ask them to self-organize and thereby determine what they can accomplish, you can establish a reliable and repeatable flow of work. 6. Respect People. Sustainable advantage is gained from engaged, thinking people. The implication is that you need a human resources strategy which is specific to IT, that you need to focus on enabling teams not on controlling them. 7. Optimize the Whole. If you want to govern your development efforts effectively you must look at the bigger picture, not just individual project teams. You need to understand the high-level business process which the individual systems support, processes which often cross multiple systems. You need to manage programs of interrelated systems so that you can deliver a complete product to your stakeholders. Measurements should address how well you’re delivering business value, because that is the raison d’etre of your IT department.
Based on our experiences, and guided by the 7 principles, Per Kroll and I identified 18 practices of lean development governance. We've organized these practices into 6 categories:1. The Roles & Responsibilities category: - Promote Self-Organizing Teams. The best people for planning work are the ones who are going to do it. - Align Team Structure With Architecture. The organization of your project team should reflect the desired architectural structure of the system you are building to streamline the activities of the team.
2. The Organization category: - Align HR Policies With IT Values. Hiring, retaining, and promoting technical staff requires different strategies compared to non-technical staff. - Align Stakeholder Policies With IT Values. Your stakeholders may not understand the implications of the decisions that they make, for example that requiring an “accurate” estimate at the beginning of a project can dramatically increase project risk instead of decrease it as intended.
3. The Processes category: - Adapt the Process. Because teams vary in size, distribution, purpose, criticality, need for oversight, and member skillset you must tailor the process to meet a team’s exact needs. - Continuous Improvement. You should strive to identify and act on lessons learned throughout the project, not just at the end. - Embedded Compliance. It is better to build compliance into your day-to-day process, instead of having a separate compliance process that often results in unnecessary overhead. - Iterative Development. An iterative approach to software delivery allows progressive development and disclosure of software components, with a reduction of overall failure risk, and provides an ability to make fine-grained adjustment and correction with minimal lost time for rework. - Risk-Based Milestones. You want to mitigate the risks of your project, in particular business and technical risks, early in the lifecycle. You do this by having throughout your project several milestones that teams work toward.
4. The Measures category: - Simple and Relevant Metrics. You should automate metrics collection as much as possible, minimize the number of metrics collected, and know why you’re collecting them. - Continuous Project Monitoring. Automated metrics gathering enables you to monitor projects and thereby identify potential issues so that you can collaborate closely with the project team to resolve problems early.
5. The Mission & Principles category: - Business-Driven Project Pipeline. You should invest in the projects that are well-aligned to the business direction, return definable value, and match well with the priorities of the enterprise. - Pragmatic Governance Body. Effective governance bodies focus on enabling development teams in a cost-effective and timely manner. They typically have a small core staff with a majority of members being representatives from the governed organizations. - Staged Program Delivery. Programs, which are collections of related projects, should be rolled out in increments over time. Instead of holding back a release to wait for a subproject, each individual subprojects must sign up to predetermined release date. If the subproject misses it skips to the next release, minimizing the impact to the customers of the program. - Scenario-Driven Development. By taking a scenario-driven approach, you can understand how people will actually use your system, thereby enabling you to build something that meets their actual needs. The whole cannot be defined without understanding the parts, and the parts cannot be defined in detail without understanding the whole.
6. The Polices & Standards category: - Valued Corporate Assets. Guidance, such as programming guidelines or database design conventions, and reusable assets such as frameworks and components, will be adopted if they are perceived to add value to developers. You want to make it as easy as possible for developers to comply to, and more importantly take advantage of, your corporate IT infrastructure. - Flexible Architectures. Architectures that are service-oriented, component-based, or object-oriented and implement common architectural and design patterns lend themselves to greater levels of consistency, reuse, enhanceability, and adaptability. - Integrated Lifecycle Environment. Automate as much of the “drudge work”, such as metrics gathering and system build, as possible. Your tools and processes should fit together effectively throughout the lifecycle.
The URLs for the 3 articles:Principles and Organizations: http://www.ibm.com/developerworks/rational/library/jun07/kroll/Processes and Measures: http://www.ibm.com/developerworks/rational/library/jul07/kroll_ambler/Roles and Policies: http://www.ibm.com/developerworks/rational/library/aug07/ambler_kroll/
The URL for the white paper:https://www14.software.ibm.com/webapp/iwm/web/preLogin.do?lang=en_US&source=swg-ldg
The URL for the webcast:https://www14.software.ibm.com/webapp/iwm/web/preLogin.do?lang=en_US&source=dw-c-wcsdpr&S_PKG=112907C[Read More]
ScottAmbler 120000HESD Tags:  agility-at-scale agileadopt architecture reuse disciplined-agile-deliver... soa 2 Comments 13,754 Views
A common question that I keep running into with customers is whether you can take an agile approach to service oriented architecture (SOA). The quick answer is yes, because Agile is orthogonal to the implementation technologies used. You can take an agile approach developing COBOL applications running on mainframes, fat-client Java applications, multi-tier J2EE applications, and yes, even services. Granted, it's easier to do with some technologies than others, either because of the nature of the technology or because of the supporting tools.
The long answer is "yes, but". You don't adopt an SOA approach for the sheer joy of doing so, instead you very likely want to improve the level of reuse within your organization. To succeed at SOA-driven reuse you need an enterprise focus, something that doesn't appear to be very common on many agile teams. Therein lies the challenge. Several strategies for improving your chances with Agile SOA, and SOA in general, follows:1. Invest in some initial enterprise architecture modeling. You don't need to identify all of the details up front, that would take too long and actually put the effort at risk, but you do need to set a starting point to guide development teams. Identifying the technical architecture is critical, and identifying a few basic services which would provide immediate business value to one or more teams is critical. Involve people from several application project teams to ensure that you get a wide range of input. See http://www.agiledata.org/essays/enterpriseArchitecture.html for a streamlined approach to enterprise architecture modeling. Creating big, detailed models often proves to be a waste of time because development teams are rarely motivated to read mounds of documentation.2. Build out the initial infrastructure on a real application development project. This proves that your SOA strategy actually works and puts the technical foundation in place for future teams. During this period you'll be tempted to try to support several development teams, which is feasible but dramatically increases your risk. It's also tempting to focus simply on getting the infrastructure in place without delivering any business functionality, but this risks producing an ivory-tower architecture that nobody is interested in.3. Spread the service architects out onto application development teams. The people that formulated and then proved your SOA should be actively involved on the development teams that are working with it to ensure that the teams use it appropriately and to ensure that the architects get concrete feedback which they can use to evolve the architecture. When working on agile teams, these people will need to work in a collaborative and evolutionary approach just like other team members.4. Fund reuse separately. I've lost track of the number of organizations that I've run into that fail at reuse because their development teams never have the resources to develop reusable assets. That's simply the nature of the beast -- project teams will always be more interested in addressing their own specific requirements than they are in investing the time and effort to make something reusable. The real problem here is that you expect them to act differently. A better strategy is to have a separate reuse engineering team that has the resources to monitor existing projects to look for potentially reusable assets. When they find said assets this team does the work to harvest the asset, to reengineer it to make it reusable, and then to integrate back into the original source project. The goal is to make it as painless as possible to produce reusable assets such as services. If you expect project teams to do this work out of the goodness of their hearts then you're effectively punishing them when they do the right thing. That's not a very good governance strategy, IMHO.5. The reuse team now owns the asset. Any reusable asset, including services, will need to be maintained, evolved over time, and supported. This isn't free nor is it viable for project teams to do so.
If you're interested, I provide agile strategies for both enterprise architecture and strategic reuse in the book "Enterprise Unified Process". Although written under the assumption that you're taking a RUP-based approach to development, the reality is that the EUP can extend any evolutionary/agile software development process so that it addresses the larger-scale needs of modern IT organizations.
- Scott[Read More]