Domain engineering

Last updated

Domain engineering, is the entire process of reusing domain knowledge in the production of new software systems. It is a key concept in systematic software reuse and product line engineering . A key idea in systematic software reuse is the domain. Most organizations work in only a few domains. They repeatedly build similar systems within a given domain with variations to meet different customer needs. Rather than building each new system variant from scratch, significant savings may be achieved by reusing portions of previous systems in the domain to build new ones.

Contents

The process of identifying domains, bounding them, and discovering commonalities and variabilities among the systems in the domain is called domain analysis. This information is captured in models that are used in the domain implementation phase to create artifacts such as reusable components, a domain-specific language, or application generators that can be used to build new systems in the domain.

In product line engineering as defined by ISO26550:2015, the Domain Engineering is complemented by Application Engineering which takes care of the life cycle of the individual products derived from the product line. [1]

Purpose

Domain engineering is designed to improve the quality of developed software products through reuse of software artifacts. [2] Domain engineering shows that most developed software systems are not new systems but rather variants of other systems within the same field. [3] As a result, through the use of domain engineering, businesses can maximize profits and reduce time-to-market by using the concepts and implementations from prior software systems and applying them to the target system. [2] [4] The reduction in cost is evident even during the implementation phase. One study showed that the use of domain-specific languages allowed code size, in both number of methods and number of symbols, to be reduced by over 50%, and the total number of lines of code to be reduced by nearly 75%. [5]

Domain engineering focuses on capturing knowledge gathered during the software engineering process. By developing reusable artifacts, components can be reused in new software systems at low cost and high quality. [6] Because this applies to all phases of the software development cycle, domain engineering also focuses on the three primary phases: analysis, design, and implementation, paralleling application engineering. [7] This produces not only a set of software implementation components relevant to the domain, but also reusable and configurable requirements and designs. [8]

Given the growth of data on the Web and the growth of the Internet of Things, a domain engineering approach is becoming relevant to other disciplines as well. [9] The emergence of deep chains of Web services highlights that the service concept is relative. Web services developed and operated by one organization can be utilized as part of a platform by another organization. As services may be used in different contexts and hence require different configurations, the design of families of services may benefit from a domain engineering approach.

Phases

Domain engineering as compared to application engineering. The outputs of each phase of domain engineering feed into both subsequent phases of domain engineering as well as corresponding phases in application engineering. Domain Engineering vs Application Engineering.svg
Domain engineering as compared to application engineering. The outputs of each phase of domain engineering feed into both subsequent phases of domain engineering as well as corresponding phases in application engineering.

Domain engineering, like application engineering, consists of three primary phases: analysis, design, and implementation. However, where software engineering focuses on a single system, domain engineering focuses on a family of systems. [7] A good domain model serves as a reference to resolve ambiguities later in the process, a repository of knowledge about the domain characteristics and definition, and a specification to developers of products which are part of the domain. [10]

Domain analysis

Domain analysis is used to define the domain, collect information about the domain, and produce a domain model. [11] Through the use of feature models (initially conceived as part of the feature-oriented domain analysis method), domain analysis aims to identify the common points in a domain and the varying points in the domain. [12] Through the use of domain analysis, the development of configurable requirements and architectures, rather than static configurations which would be produced by a traditional application engineering approach, is possible. [13]

Domain analysis is significantly different from requirements engineering, and as such, traditional approaches to deriving requirements are ineffective for development of configurable requirements as would be present in a domain model. To effectively apply domain engineering, reuse must be considered in the earlier phases of the software development life cycle. Through the use of selection of features from developed feature models, consideration of reuse of technology is performed very early and can be adequately applied throughout the development process. [14]

Domain analysis is derived primarily from artifacts produced from past experience in the domain. [11] Existing systems, their artifacts (such as design documents, requirement documents and user manuals), standards, and customers are all potential sources of domain analysis input. [11] [15] However, unlike requirements engineering, domain analysis does not solely consist of collection and formalization of information; a creative component exists as well. During the domain analysis process, engineers aim to extend knowledge of the domain beyond what is already known and to categorize the domain into similarities and differences to enhance reconfigurability. [11]

Domain analysis primarily produces a domain model, representing the common and varying properties of systems within the domain. [11] The domain model assists with the creation of architectures and components in a configurable manner by acting as a foundation upon which to design these components. [16] An effective domain model not only includes the varying and consistent features in a domain, but also defines the vocabulary used in the domain and defines concepts, ideas and phenomena, within the system. [11] [17] Feature models decompose concepts into their required and optional features to produce a fully formalized set of configurable requirements. [18]

Domain design

Domain design takes the domain model produced during the domain analysis phase and aims to produce a generic architecture to which all systems within the domain can conform. [19] In the same way that application engineering uses the functional and non-functional requirements to produce a design, the domain design phase of domain engineering takes the configurable requirements developed during the domain analysis phase and produces a configurable, standardized solution for the family of systems. Domain design aims to produce architectural patterns which solve a problem common across the systems within the domain, despite differing requirement configurations. [20] In addition to the development of patterns during domain design, engineers must also take care to identify the scope of the pattern and the level to which context is relevant to the pattern. Limitation of context is crucial: too much context results in the pattern not being applicable to many systems, and too little context results in the pattern being insufficiently powerful to be useful. [21] A useful pattern must be both frequently recurring and of high quality. [22]

The objective of domain design is to satisfy as many domain requirements as possible while retaining the flexibility offered by the developed feature model. The architecture should be sufficiently flexible to satisfy all of the systems within the domain while rigid enough to provide a solid framework upon which to base the solution. [23]

Domain implementation

Domain implementation is the creation of a process and tools for efficiently generating a customized program in the domain.

Criticism

Domain engineering has been criticized for focusing too much on "engineering-for-reuse" or "engineering-with-reuse" of generic software features rather than concentrating on "engineering-for-use" such that an individual's world-view, language, or context is integrated into the design of software. [24]

See also

Related Research Articles

<span class="mw-page-title-main">Software architecture</span> High level structures of a software system

Software architecture is the set of structures needed to reason about a software system and the discipline of creating such structures and systems. Each structure comprises software elements, relations among them, and properties of both elements and relations.

<span class="mw-page-title-main">Spiral model</span> Software development process model

The spiral model is a risk-driven software development process model. Based on the unique risk patterns of a given project, the spiral model guides a team to adopt elements of one or more process models, such as incremental, waterfall, or evolutionary prototyping.

Software design is the process by which an agent creates a specification of a software artifact intended to accomplish goals, using a set of primitive components and subject to constraints. The term is sometimes used broadly to refer to "all the activity involved in conceptualizing, framing, implementing, commissioning, and ultimately modifying" the software, or more specifically "the activity following requirements specification and before programming, as ... [in] a stylized software engineering process."

The rational unified process (RUP) is an iterative software development process framework created by the Rational Software Corporation, a division of IBM since 2003. RUP is not a single concrete prescriptive process, but rather an adaptable process framework, intended to be tailored by the development organizations and software project teams that will select the elements of the process that are appropriate for their needs. RUP is a specific implementation of the Unified Process.

Software development is the process of conceiving, specifying, designing, programming, documenting, testing, and bug fixing involved in creating and maintaining applications, frameworks, or other software components. Software development involves writing and maintaining the source code, but in a broader sense, it includes all processes from the conception of the desired software through the final manifestation, typically in a planned and structured process often overlapping with software engineering. Software development also includes research, new development, prototyping, modification, reuse, re-engineering, maintenance, or any other activities that result in software products.

<span class="mw-page-title-main">Systems development life cycle</span> Systems engineering terms

In systems engineering, information systems and software engineering, the systems development life cycle (SDLC), also referred to as the application development life cycle, is a process for planning, creating, testing, and deploying an information system. The SDLC concept applies to a range of hardware and software configurations, as a system can be composed of hardware only, software only, or a combination of both. There are usually six stages in this cycle: requirement analysis, design, development and testing, implementation, documentation, and evaluation.

In software project management, software testing, and software engineering, verification and validation (V&V) is the process of checking that a software system meets specifications and requirements so that it fulfills its intended purpose. It may also be referred to as software quality control. It is normally the responsibility of software testers as part of the software development lifecycle. In simple terms, software verification is: "Assuming we should build X, does our software achieve its goals without any bugs or gaps?" On the other hand, software validation is: "Was X what we should have built? Does X meet the high-level requirements?"

In computer programming, a software framework is an abstraction in which software, providing generic functionality, can be selectively changed by additional user-written code, thus providing application-specific software. It provides a standard way to build and deploy applications and is a universal, reusable software environment that provides particular functionality as part of a larger software platform to facilitate the development of software applications, products and solutions.

Object-oriented analysis and design (OOAD) is a technical approach for analyzing and designing an application, system, or business by applying object-oriented programming, as well as using visual modeling throughout the software development process to guide stakeholder communication and product quality.

A software factory is a structured collection of related software assets that aids in producing computer software applications or software components according to specific, externally defined end-user requirements through an assembly process. A software factory applies manufacturing techniques and principles to software development to mimic the benefits of traditional manufacturing. Software factories are generally involved with outsourced software creation.

In software engineering, domain analysis, or product line analysis, is the process of analyzing related software systems in a domain to find their common and variable parts. It is a model of wider business context for the system. The term was coined in the early 1980s by James Neighbors. Domain analysis is the first phase of domain engineering. It is a key method for realizing systematic software reuse.

Model-driven engineering (MDE) is a software development methodology that focuses on creating and exploiting domain models, which are conceptual models of all the topics related to a specific problem. Hence, it highlights and aims at abstract representations of the knowledge and activities that govern a particular application domain, rather than the computing concepts.

Product-family engineering (PFE), also known as product-line engineering, is based on the ideas of "domain engineering" created by the Software Engineering Institute, a term coined by James Neighbors in his 1980 dissertation at University of California, Irvine. Software product lines are quite common in our daily lives, but before a product family can be successfully established, an extensive process has to be followed. This process is known as product-family engineering.

Object-oriented design (OOD) is the process of planning a system of interacting objects for the purpose of solving a software problem. It is one approach to software design.

<span class="mw-page-title-main">View model</span>

A view model or viewpoints framework in systems engineering, software engineering, and enterprise engineering is a framework which defines a coherent set of views to be used in the construction of a system architecture, software architecture, or enterprise architecture. A view is a representation of the whole system from the perspective of a related set of concerns.

Software requirements for a system are the description of what the system should do, the service or services that it provides and the constraints on its operation. The IEEE Standard Glossary of Software Engineering Terminology defines a requirement as:

  1. A condition or capability needed by a user to solve a problem or achieve an objective.
  2. A condition or capability that must be met or possessed by a system or system component to satisfy a contract, standard, specification, or other formally imposed document.
  3. A documented representation of a condition or capability as in 1 or 2.

In software development, a feature model is a compact representation of all the products of the Software Product Line (SPL) in terms of "features". Feature models are visually represented by means of feature diagrams. Feature models are widely used during the whole product line development process and are commonly used as input to produce other assets such as documents, architecture definition, or pieces of code.

In software engineering, a software development process is a process of planning and managing software development. It typically involves dividing software development work into smaller, parallel, or sequential steps or sub-processes to improve design and/or product management. It is also known as a software development life cycle (SDLC). The methodology may include the pre-definition of specific deliverables and artifacts that are created and completed by a project team to develop or maintain an application.

Feature oriented domain analysis (FODA) is a domain analysis method which introduced feature modelling to domain engineering. FODA was developed in 1990 following several U.S. Government research projects. Its concepts have been regarded as critically advancing software engineering and software reuse.

Knowledge-based configuration, or also referred to as product configuration or product customization, is an activity of customising a product to meet the needs of a particular customer. The product in question may consist of mechanical parts, services, and software. Knowledge-based configuration is a major application area for artificial intelligence (AI), and it is based on modelling of the configurations in a manner that allows the utilisation of AI techniques for searching for a valid configuration to meet the needs of a particular customer.

References

  1. ISO 26550:2015 – Software and systems engineering — Reference model for product line engineering and management.
  2. 1 2 Frakes & Kang 2007 , p. 2
  3. Frakes & Kang 2007 , p. 1
  4. Czarnecki & Eisenecker 2000 , p. 19
  5. Batory et al. 2002 , p. 19
  6. Czarnecki & Eisenecker 2000 , p. 20
  7. 1 2 Czarnecki & Eisenecker 2000 , p. 21
  8. Harsu 2002 , p. 8
  9. Reinhartz-Berger et al. 2013 , p. xii
  10. Falbo, Guizzardi & Duarte 2002 , p. 2
  11. 1 2 3 4 5 6 Czarnecki & Eisenecker 2000 , p. 23
  12. Czarnecki & Eisenecker 2000 , p. 38
  13. Kang et al. 2004 , p. 7
  14. Kang et al. 2004 , p. 3
  15. Kang et al. 2004 , p. 4
  16. Frakes & Kang 2007 , p. 3
  17. Czarnecki & Eisenecker 2000 , p. 84
  18. Czarnecki & Eisenecker 2000 , p. 86
  19. Czarnecki & Eisenecker 2000 , p. 24
  20. Czarnecki & Eisenecker 2000 , p. 25
  21. Buschmann, Henney & Schmidt 2007 , p. 42
  22. Buschmann, Henney & Schmidt 2007 , p. 31
  23. Czarnecki & Eisenecker 2000 , p. 28
  24. Mettler 2017 , p. 5

Sources