The Economics of Reuse

Objectives

Reusing artifacts means using them in contexts that are different of their native ones. That may come by design, when specifications can anticipate on shared concerns, or as an afterthought, when initially unexpected similarities are identified later on.

Economics of Reuse (Sergio Silva)
Economics of Reuse (Sergio Silva)

Planned or opportunistic, reuse brings benefits in terms of costs, quality, and continuity:

  • Cost benefits are most easily achieved for component engineering but may also be obtained upstream with model reuse and patterns.
  • Quality benefits are first and foremost rooted at model level, especially when components implementation is supported by automated tools.
  • Continuity benefits are to be found both along the business (semantics and business rules) and engineering (functional architecture and platform implementations) perspectives.

Reuse policies may also bring positive externalities by inducing a comprehensive approach to software design.

Yet, those policies will usually entail costs and may as well bear negative externalities:

  • Artifacts designed for reuse are usually most costly to develop, even if part of additional costs should be ascribed to quality management.
  • Excessive enforcement policies may significantly hamper projects ability to meet business needs in time.
  • Managing reusable assets usually induces overheads.

In order to assess those policies, economics of reuse must be set across business, engineering or architecture perspectives:

  • Business perspective: how to factor out and reuse artifacts associated with the knowledge of business domains when system functionalities or platforms are modified.
  • Engineering perspective: how to reuse development artifacts when business contents or system platforms are modified.
  • Architecture perspective: how to use system components independently of changes affecting business contents or development artifacts.

That can be achieved by managing development assets along model driven architecture: CIMs for business and enterprise architecture, PIMs for systems functional architecture, and PSMs for systems technical architecture.

Contexts & Concerns

Whatever their inception, reused artifacts are meant to be used independently of their native context and concerns: opportunistic reuse will map a specific purpose to another one, planned reuse will map a shared concern to a specific purpose. As a corollary, reuse policies must be supported by some traceability mechanism linking concerns and purposes across contexts and architectures.

From the enterprise perspective, the problem is to reuse the knowledge of business domains and processes. For that purpose different mechanisms can be considered:

  • The simplest solution is to reuse generic components, with the business knowledge directly transferred through parameters.
  • Similarly, business rules can be separately edited and managed in business contexts before being executed by system components.
  • One step further, business semantics and rules can be fenced off with domains and applied to different objects and applications.
  • Finally, models of business objects and processes can be capitalized and managed as reusable assets.
Reuse Policies with Model Driven Architecture

Once business knowledge is duly capitalized as functional assets, they can be reused along the engineering perspective:

  • System functionalities: functional patterns are (re)used to map functional requirements to functional architecture, and services are (re)used to support business processes.
  • Software architecture: Object and aspect oriented designs, using inheritance and polymorphism.
  • Software implementations: Component-based development and information hiding.

Along the architecture perspective information hiding is generalized to systems, and reuse is masked by the definition of services.

It must be noted that, contrary to misleading similarities, refactoring is the opposite of reuse: instead of building from well understood and safe artifacts, it tries to extract some reusable chunks from opaque and unsafe components.

Knowledge Reuse

Enterprise and business knowledge may affect the full scope of system functionalities: boundaries (e.g users authorizations), controls (e.g accounting rules), and persistency (e.g consistency constraints). Whereas there isn’t much to argue about the benefits of reusing enterprise and business knowledge, costs may significantly diverge depending on the way corresponding assets are managed:

  • Domain specific knowledge are rooted at requirements level. That’s typically achieved when use cases are introduced to describe how systems are meant to support business processes. With different use cases targeting different aspects of the same business objects and processes, overlaps must be identified and factored out in order to be reused across processes.
  • Business knowledge may also be global, i.e shared at enterprise architecture level, defining objectives, assets and organization associated with the continuity of corporate identity and business capabilities within a regulatory and market environment.
Use cases access to respectively shared (a,b) and specific (c,d) knowledge for objects and application domains

In any case, the challenge is to map business knowledge to system models, more precisely to embed reused descriptions of business objects and process to corresponding development artifacts. At architecture level the mapping should target objects or processes identities, at domain level the focus will be on aspects and views.

As epitomized by service oriented architectures, business architectures can be mapped to system ones through delegation, either directly (business processes calling on services), or indirectly (collaboration between services). That will establish a clear distinction between shared (aka global) and domain specific knowledge, and consequently between respective economics of reuse.

  • Given that shared knowledge must be reused across domains and applications, there can be no argument about benefits. That will be achieved by a messaging model built on a need-to-know basis. And since such model is an intrinsic feature of the functional architecture, it incurs no additional overheads.
  • Specific knowledge for its part is managed at domain level and therefore masked behind services interfaces. Whatever reuse occurs there remains local and an intrinsic part of domain design.
Knowledge Reuse through services (a), boundaries (b), controls (c), and entities (d).

Things are not so clear when business knowledge is not managed by services but distributed across domains, mixing specific and global knowledge. Managing reusable assets would be easy were the distinction between business and functional requirements to coincide with the one between shared and specific knowledge; unfortunately that’s seldom the case, and requirements, functional or business, will have to be sorted out at architecture or design level.

Whereas Service Oriented Architectures (SOA) put functionalities in the driving seat, Enterprise Application Integration (EAI) gives the lead to applications for which it provides adapters. As maintenance of integration adapters is a very poor substitute for knowledge management, reuse is mostly limited to legacy applications.

Maintaining adapters across layers of applications induces significant overheads

At design level knowledge is weaved into canonical data models (entities), functional architectures (controls), and user interfaces frameworks (boundaries).

Mixed concerns: business requirements can be specific, functional ones can be global.

On one hand, tracing reuse to requirements may be problematic as they are by nature concrete and unstructured, hence not the best support for generalization or the factoring out of shared features. Assuming business analysts can nonetheless separate reusable wheat from specific chaff, knowledge management at this level will require a dedicated framework supporting comprehensive and differentiated traceability. Additional overheads will have to be taken into account and compared to potential benefits.

On the other hand, canonical data models and functional architectures are meant to provide unified views of shared objects and semantic domains. Yet, canonical models are by nature unwieldy as they carve structures, features, and connections of business objects, without clear mechanisms to combine shared and specific knowledge. As a corollary, their use may reduce flexibility, and their management usually induces significant overheads.

Artifacts Reuse

With enterprise and business knowledge capitalized as development assets, the engineering case for reuse may appears indisputable, but business cases are often much more controversial due to large overheads and fleeting returns. Taking cues from Barry Boehm (“Managing Software Productivity and Reuse”),  here are some of the main pitfalls of artifacts reuse:

  • Repository delusion: knowledge being by nature contextual, its reuse is driven by circumstances and purposes; as a consequence the availability of large repositories of development assets will probably be ignored without clear pointers rooted in contexts and concerns.
  • Confusion between components (or structures) and functionalities (or interfaces): under the influence of the object oriented paradigm, the distinction between objects and aspects is all too often forgotten. That’s unfortunate as this difference is congruent with the one between business objects on one hand, business operations on the other hand.
  • Over generalization: reuse is usually achieved by factoring out useful aspects or factoring off useless ones. In both cases the temptation is to repeat the operation until nothing could be added to the scope. Such “flight for abstraction” will inevitably overtake the proper level of reuse and begets models void of any anchor to business relevancy.
  • Scalability: while reuse is about separation of concerns and complexity management, those two criteria don’t have to pull in the same direction. When they don’t, variants will be dispersed across artifacts and their processing will suffer a combinatorial explosion if the system has to be scaled up.
  • Obsolescence: shelf lives of development assets can be defined by each or both business or technical relevancy. Assuming spans either coincide or are managed independently, they should be explicitly taken into account before any reuse.

Those obstacles can be managed providing that models:

Sorting out reuse concerns with differentiated inheritance.

Economics of Reuse and Sustainable Development

Sustainable system development is the ability to meet present business requirements while enhancing system capability to support future ones. Clearly reuse is not the only factor of sustainability, with architectures, returns, and risk management being pivotal. But the economics of reuse encompass most of other factors.

Architectures are clearly first to be considered, as epitomized by MDA:

  • Reuse of development assets rooted in enterprise architecture is not an option: system functionalities are meant to support business processes as they are (a).
  • At the other end of the development process, reuse of software designs and components across technical architectures should bring benefits in quality and costs (c).
  • In between reuse of system functionalities is necessary to guarantee the robustness and continuity of functional architectures; it should also leverage the benefits of reuse of enterprise and development assets (b).
Reuse of models is at the core of the MDA framework
Reuse of models is at the core of the MDA framework

Regarding returns, reuse through generic components, rules engines, or semantic domains can be directly supported by development tools, bypassing explicit models of functional architectures. That makes their costs/benefits analysis both simpler and well circumscribed. That is not the case for system functionalities which stand at the hub of perspectives. As a consequence, costs/benefits should be analyzed as a whole:

  • Regarding business assets, a clear distinction must be maintained between specific and shared knowledge, reuse being considered for the latter only.
  • Regarding the reuse of business assets as functional ones, services clearly offer the best returns. Otherwise costs/benefits are to be assessed, from reuse of vocabulary and semantics domains (straightforward, limited overheads), to canonical models and enterprise application integration (contingent, significant overheads).
  • Economics of reuse will ultimately be set by traceability mechanisms linking enterprise and business knowledge on one hand, components designs on the other hand. Even for services (c), if at a lesser degree, the business case for reuse will be decided by leveraged benefits and non cumulative costs. Hence the importance of maintaining the distinction between identified structures and associated aspects from business (a) and functional (b) requirements, to components interfaces (d) and structures (e).
Maintaining the distinction between structures and aspects from business (a) and functional (b) requirements, to components interfaces (d) and structures (e).

Finally, reuse may also play a significant role in risk management, especially when risks are managed according to their source:

  • Changes in business contexts can usually occurs along two frequency waves: short, for market opportunities, and long, for an organization’s continuity. Associated risks could be better managed if corresponding knowledge were managed accordingly.
  • System architectures are meant to evolve in synch with organization continuity; were technological environment or corporate structures subject to unexpected changes, reusable functional assets would be of great help.
  • Given that enterprise IT can no longer be self-contained and operate in isolation, reusable designs may provide buffers to technological risks and help exploiting unexpected business opportunities.

Further Reading

The Cases for Reuse

Objective

Reuse of development artifacts can come by design or as an afterthought. While in the latter case artifacts may have been originally devised for specific contexts and purposes, in the former case they would have been originated by shared concerns and designed according architectural constraints and mechanisms.

Reinventing the Wheel ? (Ready-made, M. Duchamp)

Architectures for their part are about stable and sound assets and mechanisms meant to support activities which, by nature, must be adaptable to changing concerns. That is precisely what reusable assets should be looking for, and that may clarify the rationale supporting models and languages:

  1. Why models: to describe shared (i.e reused) artifacts along development processes.
  2. Why non specific languages: to support the sharing of models across business domains and organizational units.
  3. Why model layers: to manage reusable development assets according architectural concerns.

Reuse Perspective: Business Domains vs Development Artifacts

As already noted, software artifacts incorporate contents from two perspectives:

  • Domain models describe business objects and processes independently of the way they are supported by systems.
  • Development models describe how to design and implement system components.
Artifacts reflect external as well as development concerns.

As illustrated by agile methods and domain specific languages, that distinction can be ignored when applications are self-contained and projects ownership is shared. In that case reusable assets are managed along business domains, functional architectures are masked, and technical ones are managed by development tools.

Otherwise, reusable assets would be meaningless, even counterproductive, without being associated with clearly defined objectives:

  • Domain models and business processes are meant to deal with business objectives, for instance, how to assess insurance premiums or compute missile trajectory.
  • System functionalities lend a hand in solving business problems. Use cases are widely used to describe how systems are to support business processes, and system functionalities are combined to realize use cases.
  • Platform components provide technical solutions as they achieve targeted functionalities for different users, within distributed locations, under economic constraints on performances and resources.
Problems and solutions must be set along architecture layers
Context and purpose of reusable assets

Whatever the basis, design or afterthought, reusing an artifact comes as a solution to a specific problem: how to support business requirements, how to specify system functionalities, how to implement system components. Describing problems and solutions along architecture layers should therefore be the backbone of reusable assets management.

Model and Architecture Layers

According model driven architecture principles, models should be organized around three layers depending on contents:

  • Computation independent models (CIMs) describe business objects and processes independently of the way they are supported by system functionalities. Contents are business specific that can be reused when functional architectures are modified (a). Business specific contents (e.g business rules) can also be reused when changes do not affect functional architectures and may therefore be directly applied to platform specific models (c).
  • Platform independent models (PIMs) describe system functionalities independently of supporting platforms. They are reused to design new supporting platforms (b).
  • Platform specific models (PSMs) describe software components. They are used to implement software components to be deployed on platforms (d).
Model and Architecture Layers

Not by chance, invariants within model layers can also be associated with corresponding architectures:

  • Enterprise architecture (as described by CIMs) deals with objectives, assets and organization associated with the continuity of corporate identity and business capabilities within a regulatory and market environment.
  • Functional architecture (as described by PIMs) deals with the continuity of systems functionalities and mechanisms supporting business processes.
  • Technical architecture (as described by PSMs) deals with the feasibility, interoperability, efficiency and economics of systems operations.

That makes architecture invariants the candidates of choice for reusable assets.

Enterprise Architecture Assets

Systems context and purposes are set by enterprise architecture. From an engineering perspective reusable assets  (aka knowledge) must include domains, business objects, activities, and processes.

  • Domains are used to describe the format and semantics of elementary features independently of objects and activities.
  • Business objects identity and consistency must be maintained along time independently of supporting systems. That’s not the case for features and rules which can be modified or extended.
  • Activities (and associated roles) describe how business objects are to be processed. Semantics and records have to be maintained along time but details of operations can change.
  • Business processes and events describe how activities are performed.
Enterprise Architecture Assets (anchors and semantic domains)

As far as enterprise architecture is concerned, structure and semantics of reusable assets should be described independently of system modeling methods.

Structures can be unambiguously described with standard connectors for composition, aggregation and reference,  and variants by subsets and power-types, both for static and dynamic partitions.

Combining Object and Aspect Oriented principles, reuse of enterprise architecture assets should distinguish between identities and structures on one hand, semantics on the other hand.

With regard to business activities, semantics are set by targets:

  • Processing of physical objects.
  • Processing of notional objects.
  • Agents decisions.
  • Processing of events.
  • Computations.
  • Control of processes execution.

Regarding business objects, semantics are set by what is represented:

  • State of physical objects.
  • State of notional object.
  • History of roles.
  • Events.
  • Computations.
  • Execution states.
Enterprise Architecture Assets (with variants and stereotypes)

Enterprise assets are managed according identification, structure, and semantics, as defined along a business perspective. When reused as development artifacts the same attributes will have to be mapped to an engineering perspective.

Use Cases: A bridge between Enterprise and System Architectures

Systems are supposed to support the continuity and consistency of business processes independently of platforms technologies. For that purpose two conditions must be fulfilled:

  1. Identification continuity of business domains: objects identities are kept in sync with their system representations all along their life-cycle, independently of changes in business processes.
  2. Semantic continuity of functional architectures: the history of system representations can be traced back to associated business operations.

Hence, it is first necessary to anchor requirements objects and activities to persistency and functional execution units.

Reusing persistency and functional units to anchor new requirements to enterprise architecture.

Once identities and semantics are properly secured, requirements can be analyzed along standard architecture levels: boundaries (transient objects, local execution), controls (transient objects, shared execution), entities (persistent objects, shared execution).

The main objective at this stage is to identify shared functionalities whose specification should be factored out as candidates for reuse. Three criteria are to be considered:

  1. System boundaries: no reusable assets can stand across systems boundaries. For instance, were billing outsourced the corresponding activity would have to be hid behind a role.
  2. Architecture level: no reusable assets can stand across architecture levels. For instance, the shared operations for staff interface will have to be regrouped at boundary level.
  3. Coupling: no reusable asset can support different synchronization constraint. For instance, checking in and out are bound to external events while room updates and billing are not.
Using  stereotypes to identify shared functionalities along architecture levels

It’s worth to note that the objectives of requirements analysis do not depend on the specifics of projects or methods:

  • Requirements are to be anchored to objects identities and activities semantics either through use cases or directly.
  • Functionalities are to be consolidated either within new requirements and/or with existing applications.

The Cases for Reuse

As noted above, models and non specific languages are pivotal when new requirements are to be fully or partially supported by existing system functionalities. That may be done by simple reuse of current assets or may call for the consolidation of existing and new artifacts. In any case, reusable assets must be managed along system boundaries, architecture levels, and execution coupling.

For instance, a Clean Room use case goes like: the cleaning staff manages a list of rooms to clean, checks details for status, cleans the room (non supported), and updates lists and room status.

Reuse of Functionalities

Its realization entails different kinds of reuse:

  • Existing persistency functionality, new business feature: providing a cleaning status is added to the Room entity, Check details can be reused directly (a).
  • Consolidated control functionality and delegation: a generic list manager could be applied to customers and rooms and used by cleaning and reservation use cases (b).
  • Specialized boundary functionality: staff interfaces can be composed of a mandatory header with optional panels respectively for check I/O and cleaning (c).
Reuse and Consolidation of functionalities

Reuse and Functional Architecture

Once business requirements taken into account, the problem is how to reuse existing system functionalities to support new functional requirements. Beyond the various approaches and terminologies, there is a broad consensus about the three basic functional levels, usually labelled as model, view, controller (aka MVC):

  • Model: shared and a life-cycle independent of business processes. The continuity and consistency of business objects representation must be guaranteed independently of the applications using them.
  • Control: shared with a life-cycle set by a business process. The continuity and consistency of representations is managed independently of the persistency of business objects and interactions with external agents or devices.
  • View: what is not shared with a life-cycle set by user session. The continuity and consistency of representations is managed locally (interactions with external agents or devices independently of targeted applications.
  • Service: what is shared with no life-cycle.
The Cases for Functional Reuse

Assuming that functional assets are managed along those levels, reuse can be achieved by domains, delegation, specialization, or generalization:

  • Semantic domains: shared features (addresses, prices, etc) should reuse descriptions set at business level.
  • Delegation: part of a new functionality (+) can be supported by an existing one (=).
  • Specialization: a new functionality is introduced as an extension (+) of an existing one (=).
  • Generalization: a new functionality is introduced (+) and consolidated with existing ones  (~)  by factoring out shared features (/).

It must be noted that while reuse by delegation operates at instance level and may directly affect coupling constraints on functional architectures, that’s not the case for specialization and generalization which are set at type level and whose impact can be dealt with by technical architectures.

Those options can also be mapped to agile development principles as defined by R.C. Martin:

  • Single-Responsibility Principle (SRP) : software artifacts should have only one reason to change.
  • Open-Closed Principle (OCP) : software artifacts should be open for extension, but closed for modification.
  • Liskov Substitution Principle (LSP): Subtypes must be substitutable for their base types. In other words a given set of instances must be equally mapped to types whatever the level of abstraction.
  • Dependency-Inversion principle (DIP): high level functionalities should not depend on low level ones. Both should depend on abstract interfaces.
  • Interface-Segregation Principle (ISP): client software artifacts should not be forced to depend on methods that they do not use.

Reuse by Delegation

Delegation  should be considered when different responsibilities are mixed that could be set apart. That will clearly foster more cohesive responsibilities and may also bring about abstract (i.e functional) descriptions of low level  (i.e technical) operations.

Reuse by Delegation

Reuse may be actual (the targeted asset is already defined) or forthcoming (the targeted asset has to be created). Service Oriented Architectures are the archetypal realization of reuse by delegation.

Since it operates at instance level, reuse by delegation may overlap functional layers and therefore introduce coupling constraints on data or control flows that could not be supported by targeted architectures.

Reuse by Specialization

Specialization is to be considered when a subset of objects has some additional features. Assuming base functionalities are not affected, specialization fulfills the open-closed principle. And being introduced for a subset of the base population it will also guarantee the Liskov substitution principle.

Reuse by Specialization

Reuse may be actual (a base type already exists) or forthcoming (base and subtype are created simultaneously).

Since it operates at type level, reuse by specialization is supposed to be dealt with by technical architectures. As a corollary, it should not overlap functional layers.

Reuse by Generalization

Generalization should be considered when different sets of objects share a subset of features. Contrary to delegation and specialization, it does affect existing functionalities and may therefore introduce adverse outcomes. While pitfalls may be avoided (or their consequences curbed) for boundary artifacts whose execution is self-contained, that’s more difficult for control and persistency ones, which are meant to support multiple execution within shared address spaces.

When artifacts are used to create transient objects run in self-contained contexts, generalization is straightforward and the factoring out of shared features (a) will clearly further artifacts reuse .

Reuse by generalization put open-closed and interface-segregation principles at risk.

Yet, through its side-effects, generalization may also undermine the design of the whole, for instance:

  • The open-closed principle may be at risk because when part of a given functionality is factored out, its original semantics are meant to be modified  in order to be reused by siblings. That would be the case if authorize() was to be modified for initial screen subtypes as a consequence of reusing the base screen for a new manager screen (b).
  • Reuse by generalization may also conflict with single-responsibility and interface-segregation principles when a specialized functionality is made to reuse a base one designed for its new siblings. For instance, if the standard reservation screen is adjusted to make room for manager screen it may take into account methods specific to managers (c).

Those problems may be compounded when reuse is applied to control and persistency artifacts: when a generic facility handler and the corresponding record are specialized for a new reservation targeting cars, they both reuse instantiation mechanisms and methods supporting multiple execution within shared address spaces; that is not the case for generalization as the new roots for facility handler and reservation cannot be achieved without modifying existing handler and recording of room reservations.

Reuse by Abstraction: Specialization is safer than Generalization

Since reuse through abstraction is based on inheritance mechanisms, that’s where the cases for reuse are to be examined.

Reuse by Inheritance

As noted above, reuse by generalization may undermine the design of boundaries, control, and persistency artifacts. While risks for boundaries are by nature local and limited to static descriptions, at control and persistency layers they affect instantiation mechanisms and shared execution at system level. And those those pitfalls can be circumscribed by a distinction between objects and aspects.

  • Object types describe set of identified instances. In that case reuse by generalization means that objects targeted by new artifact must be identified and structured according the base descriptions whose reuse is under consideration. From a programming perspective object types will be eventually implemented as concrete classes.
  • Aspect types describe behaviors or functionalities independently of the objects supporting them. Reuse of aspects can be understood as inheritance or composition. From a programming perspective they will be eventually implemented as interfaces or abstract classes.

Unfettered by programming languages constraints, generalization can be given consistent and unambiguous semantics. As a consequence, reuse by generalization can be introduced selectively to structures and aspects, with single inheritance for the former, multiple for the latter.

Not by chance, that distinction can be directly mapped to the taxonomy of design patterns proposed by the Gang of Four:

  • Creational designs deal with the instanciation of objects.
  • Structural designs deal with the building of structures.
  • Behavioral designs deal with the functionalities supported by objects.

Applied to boundary artifacts, the distinction broadly coincides with the one between main windows (e.g Java Frames) on one hand, other graphical user interface components on the other hand, with the former identifying users sessions. For example, screens will be composed of a common header and specialized with components for managers and staffs. Support for reservation or cleaning activities will be achieved by inheriting corresponding aspects.

Reuse of boundary artifacts through structures and aspects inheritance

Freed from single inheritance constraints, the granularity of functionalities can be set independently of structures. Combined with selective inheritance, that will directly benefit open-closed, single-responsibility and interface-segregation principles.

The distinction between identifying structures on one hand, aspects on the other hand, is still more critical for artifacts supporting control functionalities as they must guarantee multiple execution within shared address spaces. In other words reuse of control artifacts should first and foremost be about managing identities and conflicting behaviors. And that can be best achieved when instantiation, structures, and aspects are designed independently:

  • Whatever the targeted facility, a session must be created for, and identified by, each user request (#). Yet, since reservations cannot be processed independently, they must be managed under a single control (aka authority) within a single address space.
  • That’s not the case for the consultation of details which can therefore be supported by artifacts whose identification is not bound to sessions.
Reuse of control artifacts through structures and aspects inheritance

Extensions, e.g for flights, will reuse creation and identification mechanisms along strong (binding) inheritance links; generalization will be safer as it will focus on clearly defined operations. Reuse of aspects will be managed separately along weak (non binding) inheritance links.

Reuse of control artifacts through selective inheritance may be especially useful with regard to dependency-inversion principle as it will facilitate the distinction between policy, mechanism, and utility layers.

Regarding artifacts supporting persistency, the main challenge is about domains consistency, best addressed by the Liskov substitution principle. According to that principle, a given set of instances should be equivalently represented independently of the level of abstraction. For example, the same instances of facilities should be represented identically as such or according their types. Clearly that will not be possible with overlapping subsets as the number of instances will differ depending on the level of abstraction.

But taxonomies being business driven, they usually overlap when the same objects are targeted by different business domains, as could be the case if reservations were targeting transport and lodging services while facility providers were managing actual resources with overlapping services. With selective inheritance it will be possible to reuse aspects without contradicting the substitution principle.

Reuse of persistency artifacts through structures and aspects inheritance

Reuse across Functional Architecture Layers

Contrary to reuse by delegation, which relates to instances, reuse by abstraction relates to types and should not be applied across functional architecture layers lest it would break the separation of concerns. Hence the importance of the distinction between reuse of structures, which may impact on identification, and the reuse of aspects, which doesn’t.

Given that reuse of development artifacts is to be governed along architecture levels (enterprise, system functionalities, platform technologies) on one hand, and functional layers (boundaries, controls, persistency) on the other hand, some principles must be set regarding eligible mechanisms.

Two mechanisms are available for type reuse across architecture levels:

  • Semantics domains are defined by enterprise architecture and can be directly reused by functionalities.
  • Design patterns enable the transformation of functional assets into technical ones.

Otherwise reuse policies must follow functional layers:

  1. Base entities are first anchored to business objects (1), with possible subsequent specialization (1b). Generalization must distinguish between structures and aspects lest to break continuity and consistency of representations.
  2. Base controls are anchored to business activities and may reuse entities (2). They may be specialized (2b). Generalization must distinguish between structures and aspects lest to break continuity and consistency of business processes.
  3. Base boundaries are anchored to roles and may reuse controls (3). They may be specialized (3b). Generalization must distinguish between structures and aspects lest to break continuity and consistency of sessions.
Reuse across architecture layers

Further Reading