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There might be more contexts in play, for example trading is likely to be connected to some on-line stock pricing service, but that's a Trading problem! A context map is relevant about our surroundings, and we Team A are working on the Banking and Expense tracking areas of our application: we are interested only in contexts that we are directly connected to and that can affect our software.
As long as we gather more information, the map will become clearer. As mentioned before, simply acknowledging that there are different models in play within our application and that model integrity can be preserved only inside a well defined bounded context, provides a lot of value to our domain modeling perspective.
Many models lose integrity as they grow, context mapping helps a lot in this sense. There's a subtle difference in the way we use patterns here: although the definition is the same - a proven solution to a recurring problem - these do seldom represent a solution we can choose.
More often than not, organization structure will impose patterns and our only hope is to recognize them before embarking in a no-win situation. Sometimes we'll have the chance to choose the best option, or to change the existing situation, but we must be aware that changes at the organization level might require more time than our project scope will allow or simply they are beyond our possibilities.
If you're in doubt where to start from, start from the development teams. A team is probably the largest organizational unit that can efficiently share a vision on a model.
Once recognized, multiple contexts might be managed by the same team, boiling down to a mostly architectural choice. Every pattern has a different cost allocation: even if they solve similar problems connecting contexts they can't be easily swapped.
For example Anti-Corruption Layer has a footprint on the code level an extra layer and very little footprint on the organization. While a Partnership, or a Customer-Supplier would probably require less code, and a single code base, but won't work without an efficient communication channel and a well defined process.
Trying to set up a partnership without a collaborative environment, is clearly a dead end strategy. It turns out that the original definition for a Context - "The setting in which a word or a statement appears that determines its meaning" - is quite precise, and scales up from design level to architectural and organizational level without losing precision or effectiveness.
Despite some legitimate "desire of uniformity", models cannot be stretched indefinitely. Bounded Contexts provide well defined safe harbors, allowing models to grow in complexity without sacrificing conceptual integrity. As a side effect, when applied on large scale projects, a Context Map shows also implicit boundaries that exist within organizations, providing a vivid, non photoshopped, snapshot of the stage upon which our project will strive. A good context map would give you a picture of the odds against you.
You might actually know if the organization is - consciously or not - working against your project's success, even before the project starts.
As a consultant, I've found Context Mapping incredibly helpful to grasp quickly Upstream Downstream Concept Account the key details of my customers' project landscape, and as a strategic decision support tool that's what maps are for, anyway.
A context map provides a holistic overview of the system that UML or architecture diagrams completely miss, helping us to focus on choices that are really viable in your scenario without wasting money in "large scale wishful thinking". Alberto Brandolini is an Information Technology consultant and trainer, with an all-round approach to software development.
Founder and owner of Avanscoperta - a consulting and software development company based in Italy - he is also a promoter of the Italian communities about Domain Driven Design and Grails. Join a community of over , senior developers. View an example. You need to Register an InfoQ account or Login or login to post comments.
But there's so much more behind being registered. Your message is awaiting moderation. Thank you for participating in the discussion. The problem is with trying to tie DDD to the design of a single application. It is not the purpose of DDD at all. DDD is to deal with different applications that cover the domain as to the set of operations required to deal with domain specific data.
Besides, DDD is to determine the minimal set of those applications and to make sure that the determined set of the operations allows future extensions of capabilities as well as the ability to solve new tasks as those arise without redesigning the domain and the services within the domain. There are several levels of DDD. The "classical" DDD patterns such as Aggregates, Repository and so on focus on how to implement a specific domain model in the most effective and elegant way.
But not all environments are the same, some do not allow DDD techniques while some others are not worth the effort. Context mapping provides a broader view that helps to deal with a broader range of situations: one of the key advantages of context mapping is that you can use the map as a decision support tool to choose whether to apply DDD principles or not in a given portion of the application, to see if the whole project is heading towards success or if it is doomed to failure.
Ok, it's not a crystal ball Some experienced folks might be able to draw the same conclusions, but more often we realize too late that our project is on a dead end track. Context Mapping helps us asking the right questions early, to avoid incredibly costly mistakes.
As soon as you start talking about design patterns instead of capturing the domain specifics, it is exactly there you substitute the actual purpose of DDD or what existed before for over 25 years already, but was not called DDD with exploring design patterns - whether those work for your project or not.
Besides, in the current context of DDD I think the major emphasis is to be on understanding the tasks that are to be solved or supported by the domain, and from there defining the domain content - operations, interactions, etc.
It is difficult to guess whether context mapping is really something that helps to solve the task of describing the domain. Maybe, it is a true statement, but it requires more serious examples then the over-used banking account and transaction example.
Looks like I gave the wrong impression in my answer: I wanted to highlight the differences between the two pattern types, not to emphasize patterns over the domain. Let's try to do a better job. Factories and Aggregates and so on help developers to provide a clean, technology independent, implementation of the domain model so that the domain could be expressed with a higher degree of freedom.
They're useful tools in many situation, but I mean, I would never talk 'bout factories, aggregates or repositories with the domain expert, like I wouldn't talk about DAOs or annotations.
Talking about the examples, I've been thinking about different options, and what I used in the article is definitely a trade off. The problem is that Context Upstream Downstream Concept Global Mapping is a useful tool to manage complexity, but an article might not be the right container for "real world class complexity". So I looked for a somewhat simplified domain that allowed me to formulate many different examples without spending Upstream Downstream Concept Quartz so much time explaining different really complicated domains or punish innocent readers with byzantine examples from obscure domains.
Also, the first example is really trivial, I decided to keep it, because I've seen many projects where this was enough to fool some developers maybe with an active help from IDE's code completion capabilities but mostly because I wanted to show that the same principle mapped from very small coding issues, to large organizational ones.
But I have to say that Account turned out to be an ambiguous term even in one of my last projects even if the two overlapping areas were more complex and domain-specific than those I used in the example and generated a lot of noise.
The domain expert was continuously using the same term with different meaning in the same phrase, confusing every early stage conversation.
But still However, I've found that drawing a context map turns useful for different purposes. At the modeling level, it helped me to recognize the many contexts in play earlier, resulting in a cleaner understanding of the domain. In this case, we might see a Bounded Context as "a portion of the model which is completely ambiguity-free". At project management level, drawing the map guided me to ask relevant questions about the development environment and to highlight hot problem areas about the project.
Some experienced folks do ask these relevant questions by heart, but in the average project, the trickiest problems were in the white space between the contexts. They're usually there from day one, but many times everybody is so busy doing something else. Context Mapping together with distillation helps me to see whether DDD can make the difference and where", but also "we're putting a lot of effort in this area, but the result would be completely worthless if we can't improve this one too, or establish a more effective collaboration with that team.
Very interesting article! If your team is dealing with multiple contexts within a single application, you'll probably strive to make context boundaries explicit. Maybe draw the map, share it on the wall, and evolve it as the project proceeds.
Sometimes, simply being aware of the different contexts in play would make a huge difference. You'll then might want to mark distinctions in the code: make boundaries explicit, access external contexts through a translation layer, maybe behind a Service, and so on. Or to keep a shared dictionary on a Wiki, where relevant terms are explicitly associated with the contexts they belong to. But the tool choice really depends on the specific environment.
On a broader scope, where contexts are the result of organizational structure, recognizing the patterns often turns into an exercise of realpolitik. Maybe a team is expected to deliver something, but the context map is exposing its downstream relation with an unreliable team I've been there , maybe a collaboration that used to work could be put under pressure by an increased amount of work.
In this case it really depends on your influence on the organization. Sometimes you can trigger a change, some times you can but the change won't happen within the time frame of your project, some other times you have to accept that this is the reality you'll have to deal with for the next months. As I said in another thread, often organizational patterns are not the result of an explicit decision.
Sometimes simply "happen" without an official responsible person: nobody's responsible for "the white space between the contexts". This might be a problem or an opportunity. It depends. That's intimately context specific. So I can't really answer on this one. One thing I can say, though, is that the approach to domains has a lot to do with the learning process.
Sometimes i. More often, a combination of different approaches might be the best solution, but this area is a lot dependent on individuals. What a great article. Few things missing! How can we handle referential integrity among models of different context? How to handle fault tolerance? Seek Value, Not Just Savings In days long past, procurement and AP were both regarded as necessary functions that, at best, could mitigate the expense they created by focusing on creating cost savings. Bringing together powerful eProcurement powered by artificial intelligence and process automation, a procurement system can help your company build value in both directions as it: Creates a shared, cloud-based, centralized data management solution that connects all your procurement function with AP and: Integrates with your existing enterprise resource planning ERP system, accounting software, and other tools such as customer resource management CRM and marketing applications.
Makes it easy to capture, organize, review, and analyze all your spend data in real time, ensuring more accurate reports and forecasts and providing actionable insights for better decision making. Creates a closed system for buyers, connected to contract management, vendor relationship management, and supply chain management modules to ensure the correct information is always used and the best vendor is automatically provided for every good and service purchased.
Eliminates maverick spend and combats invoice fraud and theft. Improves cash flow. Makes process automation a central component of every workflow, and: Transforms paper-based manual workflows into touchless digital ones. Removes human error and delay. Speeds every workflow without sacrificing accuracy or completeness.
Frees staff to focus on high-value tasks while ensuring data entry, three-way invoice matching, and basic vendor onboarding are still handled effectively. Reduces all cycle times and enables AP to capture more early payment discounts while reducing or eliminating late fees and lost or duplicate payments. Improves vendor relationships through clear communication, tools such as vendor portals for easy access and eInvoicing, and a collaborative approach that encourages development of strategic partnerships.
Transforms upstream processes by providing a rich and easily accessible supply of data that makes it easier to build more efficient processes, pursue opportunities that might not have otherwise been readily visible, and develop a business strategy powered by strategic sourcing.
Find Out How. Download PDF. Read Blog Post. Business Strategy What is a Flat File? Examples of downstream companies include leading U. Phillips 66 was initially part of parent company ConocoPhillips COP until the larger oil company opted to spin off the downstream business in Your Money. Personal Finance.
Your Practice. Popular Courses. Oil Guide to Investing in Oil Markets. Commodities Oil. Upstream vs. Downstream Oil and Gas Production: An Overview The terms upstream and downstream oil and gas production refer to an oil or gas company's location in the supply chain.
Key Takeaways Upstream and downstream oil and gas production refer to an oil or gas company's location in the supply chain. Downstream oil and gas production engages in anything related to the post-production of crude oil and natural gas activities. Midstream links upstream and downstream and includes transportation and storage services.
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