Identities and Aspects
Despite its object and unified vocations, the OMG’s UML (Unified Modeling Language) has been sitting uneasily between scopes (e.g requirements, analysis, and design), as well as between concepts (e.g objects, aspects, and domains).
Identity vs Aspect (Mauricio Cattelan)
Those misgivings probably go a long way to explain the limited, fragmented, and shallow footprint of UML despite its clear merits. Hence the benefits to be expected from a comprehensive and consistent approach of object-oriented modeling based upon two classic distinctions:
- Business vs System: assuming that systems are designed to manage symbolic representations of business objects and processes, models should keep the distinction between business and system objects descriptions.
- Identity vs behavior: while business objects and their system counterpart must be identified uniformly, that’s not the case for aspects of symbolic representations which can be specified independently.
That two-pronged approach bridges the gap between analysis and design models, bringing about a unified perspective for concepts (objects and aspects) as well as scope (business objects and system counterparts).
Object Oriented Modeling
Object Oriented and Relational approaches are arguably the two main advances of software engineering for the last 50 years. Yet, while the latter is supported by a fully defined theoretical model, the former still mostly stands on the programming languages supporting it. That is somewhat disappointing considering the aims of the Object Management Group (OMG),
UML was born out of the merge of three modeling methods: the Booch method, the Object-modeling technique (OMT) and Object-oriented software engineering (OOSE), all strongly marked by object orientation. Yet, from inception, the semantics of objects were not clearly defined, when not explicitly confused under the label “Object Oriented Analysis and Design” (OOA/D). In other words, the mapping of business contexts to system objects, a critical modeling step if there is any, has been swept under the carpet.
That’s a lose/lose situation. Downstream, OO approaches, while widely accepted at design level, remain fragmented due to the absence of a consensus regarding object semantics outside programming languages. Upstream, requirements are left estranged from engineering processes, either forcing analysts to a leap of faith over an uncharted no man’s land, or to let business objects being chewed up by programming constructs.
Domains and Images
In mathematics, an image is the outcome of a function mapping its source domain to its target co-domain. Applied to object-oriented modeling, the problem is to translate business objects to their counterpart as system components. For that purpose one needs to:
- Define domains as sets of business objects and activities whose semantics and life-cycle are under the authority of a single organizational unit.
- Identify the objects and phenomena whose representation has to be managed, as well as the lifespan of those representations.
- Define the features (attributes or operations) to be associated to system objects.
- Define the software artifacts to be used to manage the representations and implement the features.
From Business Domain to System Image
While some of those objectives can be set on familiar grounds, the four must be reset into a new perspective.
Business Objects are rooted in Concerns
Physical or symbolic, objects and activities are set by concerns. Some may be local to enterprises, some defined by common business activities, and some set along a broader social perspective. The first step is therefore to identify the organizational units responsible for domains, objects identities and semantics:
- Domains in charge of identities will govern objects life-cycle (create and delete operations) and identification mechanisms (fetch operations). That would target objects, agents, events and processes identified independently of systems.
- Domains in charge of semantics will define objects features (read and update operations). That would target aspects and activities rooted (aka identified) through primary objects or processes.
Context anchors and associated roles and activities
It must be noted that whereas the former are defined as concrete sets of identified instances governed by unique domains, the latter may be defined independently of the objects supporting them, and therefore may be governed by overlapping concerns set by different domains.
Objects and Architectures
Not by chance, the distinction between identities and features has an architectural equivalent. Just like buildings, systems are made of supporting structures and subordinate constructs, the former intrinsic and permanent, the latter contingent and temporary. Common sense should therefore dictate a clear distinction between modeling levels, and put the focus on architectures:
- Enterprise architecture deals with objectives, assets and organization associated with the continuity of corporate identity and business capabilities within a given regulatory and market environment. That is where domains, objects and activities are identified and defined.
- Functional architecture deals with the continuity of systems functionalities as they support the continuity of business memory and operations. At this level the focus is not on business objects or activities but on functions supported by the system: communication, control, persistency, and processing.
- Technical architecture deals with the feasibility, efficiency and economics of systems operations. That is where the software artifacts supporting the functions are designed .
Objects and Architectures
Objects provide the hinges binding architectural layers, and models should therefore ensure direct and transparent mapping between business objects, functional entities, and system components. That’s not the case for features whose specification and implementation can and should be managed separately.
Fleshing out Objects with Semantic Aspects
Confusing business contexts with their system counterparts leads to mistaken equivalence between features respectively supported by business objects and system artifacts:
- The state of physical objects may be captured or modified through specific interfaces and persistently recorded by symbolic representations, possibly with associated operations.
- Non physical (notional) business objects are identified and persistently recorded as such. Their state may also appear as transient objects associated with execution states and processing rules.
- Events have no life-cycle and therefore don’t have to be identified on their own. Their value is obtained through interfaces; associated messages can be used by control or processing functions; values can be recorded persistently. Since the value of past events is not meant to be modified operations are irrelevant except for interfaces.
- Actual processes are identified by execution context and timing. There state may be queried through interfaces and recorded, but persistent records cannot be directly modified.
- Symbolic processes are identified by footprint independently of actual execution. Their execution may be called through interfaces and the results may be recorded, but persistent records cannot be directly modified.
- External roles are identified by the interfaces supporting the interactions. Their activity may be recorded, but persistent records cannot be directly modified.
Fleshing out Aspects
By introducing complementary levels of indirection between business and system objects on one hand, identities and features on the other hand, the proposed approach significantly further object-oriented modeling from requirements analysis to system design. Moreover, this approach provides a robust and effective basis for the federation of business domains, by modeling separately identities and semantic features while bridging across conceptual, logical and physical information models.
Untangling Business Rules
However tangled and poorly formulated, rules provide the substance of requirements as they express the primary constraints, needs and purposes. That jumble can usually be reshaped differently depending on perspective (business or functional requirements), timing constraints (synchronous or asynchronous) or architectural contexts; as a corollary, the way rules are expressed will have a significant impact on the functional architecture of the system under consideration. Hence, if transparency and traceability of functional and technical arbitrages are to be supported, the configuration of rules has to be rationalized from requirements inception. And that can be achieved if rules can be organized depending on their footprint: domains, instances, or attitudes.
From Objects to Artifacts
Requirements analysis is about functional architecture and business semantics, design is about software artifacts used to build system components. The former starts with concrete descriptions and winds up with abstract ones, the latter takes over the abstractions and devise their concrete implementation.
Uphill to functionalities, downhill to implementations
Somewhat counter-intuitively, information processing is very concrete as it is governed by actual concerns set from biased standpoints. Hence, trying to abstract requirements of supporting systems up to some conceptual level is a one way ticket to misunderstandings because information flows are rooted in the “Here and Now” of business concerns. Abstract (aka conceptual) descriptions are the outcome of requirements analysis, introduced when system symbolic representations are consolidated across business domains and processes.
Starting with a concrete description of identified objects and processes, partitions are used to analyze the variants and select those bound to identities. Inheritance hierarchies can organized accordingly, for objects or aspects.
Inheritance of identities vs inheritance of aspects.
While based on well understood concepts, the distinction between identity and aspect inheritance provides a principled object-oriented bridge between requirements and models free of any assumption regarding programming language semantics for abstract classes or inheritance.
Objects, attitudes, and Programming Languages
Because object-oriented approaches often stem from programming languages, their use for analysis and design is hampered by some lack of consensus and a few irrelevant concepts. That is best illustrated by two constructs, abstract classes and interfaces.
- Most programming languages define abstract classes as partial descriptions and, as a result, the impossibility to be instantiated. When applied to business objects the argument is turned around, with the consequence, no instance, taken as the definition.
- Interfaces are also a common features of object-oriented languages, but not only, as they may be used to describe the behavior of any software component.
Those distinctions can be settled when set within a broader understanding of objects and aspects, the former associated with identified instances with bound structures, eventually implemented as concrete classes, the latter with functionalities, eventually implemented as abstract classes or interfaces.
From Analysis to Design
A pivotal benefit of distinguishing between objects identity and aspects is to open a bridge between analysis and design by unifying respective patterns along object-oriented perspective. Taking a cue from the Gang of Four, system functionalities could be organized along three basic pattern categories:
- Creational functionalities deal with the life-cycle (create and delete operations) and identification mechanisms (fetch operations) of business objects whose integrity and consistency has to be persistently maintained independently of activities using them.
- Structural functionalities deal with the structure and semantics of transient objects whose integrity and consistency has to be maintained while in use by activities. They will govern features (read and update operations) and target aspects and activities rooted (aka identified) through primary objects or processes.
- Behavioral functionalities deal with the ways objects are processed.
Mapping analysis patterns to design ones will greatly enhance models traceability; moreover, taking advantage of the relative maturity of design patterns, it may also boost quality across model layers as well as the whole effectiveness of model driven engineering solutions.
Objects Oriented Modeling and Model Driven Engineering
The double distinction between contexts and systems on one hand, objects and aspects on the other hand, should help to clarify the contents of modeling layers as defined by OMG’s model driven architecture (MDA):
- Computation independent models (CIMs) are structured around business objects and processes identified on their own, associated with organizational details for roles and activities.
- Platform independent models (PIMs) are organized on two levels, one for functional architectures (boundaries, processes, persistency, services, communication), the other one for associated aspects.
- Platform specific models (PSMs) are similarly designed on two levels, one mapping functional architectures, the other one implementing aspects.
MDA with UML#
Using UML#, object-oriented concepts can therefore be applied uniformly from requirements to design without forcing programming semantics into models.