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If we had models that are traced to our requirements behind our specifications, then we could use those models to connect things that appear in diagrams, texts, and tables within our specifications. Models are simple to create if we use an approach like ISEM, although it is difficult to confirm their proprieties by analysis. However, in normal engineering systems we do not prove the properties of designs but merely trust the due diligence of the Designer.

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It is important to understand that the model only has the properties of a formal system, i. These are the properties that appear between the Aspects of Presence, Identity, and Truth. It is only when we add the Aspect of Reality that we get the crucial aspects of verifiability, validity, and coherence. Verifiability is the relationship that the model has to the requirements.

Validity represents the relationship between the model and the context of use. Coherence is the internal synergy and integrity of the model that is achieved when we add a model behind the surface presentation of a system design representation. For example, it is possible to pose questions about the design model that underlies the representation when we use an MS Powerpoint slide diagram that has been annotated with the modelling statements in a DSL.

The Powerpoint diagram cannot answer our questions, only the Designer can satisfy our queries, particularly if the slide is not annotated. As Peter Naurxxii points out, no amount of documentation can capture what the Designer has in mind, but a model can serve as a representation of the knowledge that his diagrams and pictures do not capture.

We can ask if the model is complete and consistent with itself, and if it conforms to the well-formedness rules of the representational medium. By triangulating the requirements through verification and the operational environment through validation, we can discover the coherence of the model, which is a deeper property the model has within itself because it signifies its synergy, integrity, and poise toward the environment beyond its own synthesis. Without the model it is impossible to query surface representations concerning these properties because the surface representations cannot be shown as closed.

This allows others to look at the model and to analyse it. Furthermore, the model can become a vehicle for the individual to capture and communicate his tacit knowledge, which is informing the design indirectly. Pi ture, Pla , a d Model In my dissertation I discuss the sub-schemas of Picture, Plan, and Model, which are projected as precursors of the Whole Form that is being designed. The diagrams that appear in Powerpoint designs are pictures.

They are normally global pictures of the parts of the design, or they may be pictures of the different parts of the design. In order to produce a model one must first have a plan.

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The plan like a blueprint shows the object under design from different viewpoints with the various features measured and augmented by notations. The plan allows us to know what would be repeated in different dimensions to produce the model.


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The model is usually an abstract representation of the whole system in miniature, sometimes with certain details omitted, or in some cases, as a yet non-working configuration that abstracts from the complete functioning of the final synthetic system implementation. We are advocating that we should use the ISEM language to produce plans and models that would stand behind our diagrammatic representations with the same integrity as the statements expressed in a Euclidian Proof that are isomorphic to the diagram of the proof.

To produce the plan we must construct a series of models, meta- models, and meta2-models that form the basis for the representation of the terminal or instance model. A series such as this can define what will be repeated in the representation and can be used to build up the terminal or instance model.

It defines the ontology of the domain by specifying the possible categories and elements that can appear in the model. Then, a series of meta-models will describe what kinds of relationships that these ontological elements can have with each other. These are stated in a restricted English formalism. They are posited relationships between ontological elements identified through definition statements.

These posited relationship statements can relate the elements to each other in order to make sense within the domain. Beyond these two basic statements we can also have Lemmas and Proof type statements. Lemmas are steps toward proofs; they include the relationships between statements that establish deeper structures in the modelling system. Of course, we would like to prove our designs and that is for the most part a distant goal. But, at this point, what we can do is to build up Lemmas in order to strive for a kind of closure that would allow proofs to be written about the system.

We should think of the system as a synthesis, and if that synthesis is completely closed, i. We are in a design process that posits synthesis and works toward it. We move back and forth between the analysis of the model and its representations, as well as the further elaboration of the synthesis that we are projecting on the design. Peirce makes a very interesting point that is not normally understood, which is, that there is a difference between the precision of analysis and what he calls the precission of the synthesisxxv.

What we want is a representation that will give us the most direct access as possible, and that is what ISEM attempts to give: a representation where the structure of the syntax is as simple as possible and a representation where the formal language is as direct as possible so that we can oscillate between the precision of Analysis that deconstructs the parts of the system and the precission of Synthesis that works backwards from the posited synthesis. A representation such as this will give clarity and soundness to the design and will facilitate the shared vision of the design team.

We want reviewable documents that will represent the model of the design and capture the knowledge of the system at the level of the intention of the users and stakeholders of the design. In other words, domain experts should be able to read the representation and understand it without being hampered by the clutter of the syntax of computer languages. It should represent the concepts they are working with and not some transformation of those concepts into another language or representation that is familiar only to the system architect and the software engineers. ISEM allows this oscillation between the decomposition of analysis through precision and the articulation of the projected design Synthesis by precission.

Software Language Engineering: Creating Domain-Specific Languages Using Metamodels

The design synthesis we are projecting, which is emergent, is our vision of how to build a system so that it actually works as intended for the customer and end user. This demand causes us to create new statements in our generic design model languages and domain specific languages. It may also drive us to create new languages to capture other views of the system that are either domain specific or necessary due to the technological infrastructure we are using to realize the system.

The languages that represent the models themselves are syntheses at a higher level of abstraction in the knowledge domains that support the specific system design.

Many times these knowledge domains remain tacit within the kinds of specifications we normally use to describe the systems that we build. ISEM type modelling languages attempt to make these modeling domains explicit and thus can be a means for capturing our own knowledge about various domains, or for communicating that knowledge to others in a concise form. It is a way for us to collect our own knowledge of design and to develop our own architectural styles.


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Designers could produce their own languages with a language design that supports their own knowledge, styles, and approaches toward their design. ISEM is merely one example that shows the feasibility and efficacy of such a simple and direct approach to Model Based Engineering and Domain Engineering that includes an example version of Domain Specific Languages tailored for architectural design.

Every language could be omitted, tailored, and recreated as the Designer acting as domain engineer saw fit. The high entry costs of designing parsers or graphical tools for our domain specific languages are not necessary. We can benefit from Domain Specific Languages in these Model Based Designs quickly and efficiently by using the tools we already have in a new way.

This allows us to experiment and prove our concepts before we invest in expensive tooling that we may not use, as well as avoiding the wasted time and energy spent on an approach that has been developed in a traditional manner that uses only the surface representations of our designs. The promise of model based design will give us the opportunity to use these models to generate products from our design, such as code. Eventually we want our models to become the center of the system rather than an appendage to the system. As long as the code or the material implementation of the system is the center focus, then we are stuck producing documentation that may never be used or could possibly be wrong.

However, if we eventually generate the code or material implementation from the model, then we will continue to update the models because they will become the center of the system implementation rather than an unnecessary supplement. Rather, the emphasis is on maximal expressability at the point where the Emergent Architectural Design is being visualized and synthesized. At that point we want to have a platform of a language template that we can use, although we want maximum resilience, adaptability, and flexibility in our mode of expression so that we can simultaneously be developing the representation for the design and the design itself.

Our language does not have to be able to express everything from the very beginning as programming languages do. Later, once we have a sketch of the design at some level of abstraction, then we will be able to fill in that synthesis through an analysis of the language extensions or new domain languages that we have created in the process. At a later stage we will want to formalize the languages that we are using and tighten them up by improving their formal properties. At that time we can refactor our designs based on a higher formalism and introduce models whose representations can be parsed and whose conceptual systems have the necessary formal properties we desire.

Thus, we are advocating that we allow for para-consistency, para-completeness, and para-clarity in our languages and models during the first part of the design process as we create an infrastructure that supports the design and develops along with the superstructure of the design itself. This will allow the architectural design representations and models to be fully emergent. As a model based engineering approach, ISEM embodies the technologically simplest possible way that an entire hierarchical structure of meta-models and language representations can be easily understood and easily manipulated.

There are many complex standards in this area, but these complex standards get in the way of understanding the fundamental ideas behind Model Based Engineering and Domain Specific Languages. It uses tools that everyone who operates within desktop environments will understand. It does not require any special tools that cost money beyond the bare minimum that has already been spent to support engineering work.

It allows products to be produced that can be reviewed, shared, and configuration managed. The models can be incorporated into standard engineering products such as specifications and operational concept documents. It does not use any unreadable syntax such as XML as its basis, but can easily be transformed into XML if necessary to interface with other established or future representational tools.

Model transformations could be used to move the designs that are in ISEM into other tools. Thus, designers can produce products on a small scale and then transform them into a larger representational environment as necessary. There are also other textual representations of models being developed, for example, Xtextxxvi is part of Eclipse and could be used interchangeably with ISEM or as a transformation of ISEM.

The parsing and transformation of ISEM into other graphical or textual representations is always possible. It can also be embedded in extendable languages such as M, Convergexxviii, or PIxxix. When we first attempt to capture the Emergent Architectural Design it is more important to maximize flexibility, adaptability, and resilience while the vision is still fresh. First, we may write down a description of the system design as a brief sketch.

We could make drawings on the back of envelope or on a quadpad. But then, as we articulate and solidify that design, we may want to describe it more formally in simple English by using statements that capture what we know at the time. ISEM is designed so that the various facts that you know about the design can be captured in a statement. For this reason ISEM has more statements that are absolutely necessary because it has statements that will allow each entity and each relationship to be captured independently.

For instance, if we only know that one state exists we should be able to write that down, or if we only know that there is a relationship between two states we should be able to capture that also. But eventually we may want to move toward a more concise representation where there is a single statement for each state vector in the system. ISEM allows you to discover the nature of the design as it emerges and then to consolidate the various features of the design as more information is gathered that allows the designers to make that consolidation.

It allows you to create new statements or whole languages for capturing the novel and emergent qualities of the design. It is this simple extensibility of ISEM that makes it valuable as the first responder in the design process. And we know that the process of writing allows us to discover new ideas and expand upon our design paradigms as we design.

This then allows us to apply analysis and synthesis to the representations that are created in ISEM as well as to consolidate what we have learned in the emergent process of creating the first architectural design model. Most designers study methods, languages, tools, and other applications in order to form ideas about how things can be designed. Instead, we engineers tend to make up things as we go along when we are engaged in the design process and we use methods and tools in an ad hoc fashion, first, by doing everything by hand possibly on quadpads or on pieces of paper.

We then take these thoughts and ideas and refine their sketches until we have something workable and this is the point when ISEM proves to be very useful. ISEM allows these sketches to be captured in the first formalism so that consistency and completeness checks can be done early on the sketches. Terminal or instance models may only use a small part of the available language but they are only as complex as the system that is being designed.

As the design progresses we could reduce the number of statements that are being used to express a feature of the design. Terry Halpin. Artificial Intelligence Programming. Eugene Charniak. Lisp in Small Pieces. Christian Queinnec. Raul Sidnei Wazlawick. Code Reading. Diomidis Spinellis. Relational Theory for Computer Professionals. Model-Driven Software Engineering in Practice. Marco Brambilla. Conrad Weisert. Mastering Text Mining with R.

Ashish Kumar. Introduction to Information Retrieval. Christopher D. Modern Compiler Implementation in C. Andrew W. Python Data Science Essentials. Luca Massaron. Machine Learning Algorithms. Giuseppe Bonaccorso. The Data Science Handbook. Field Cady. Developing High Quality Data Models. Matthew West. Peter Gottschling. Scientific Computing with Python 3. Claus Fuhrer. How to Design Programs.

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Matthias Felleisen. Brian Hahn. Richard K. Cyrille Rossant. Semantic Computing. Heather Yu. Systematic Program Design. Yanhong Annie Liu. Implementing Domain-Driven Design. Vaughn Vernon. Introduction to Open Core Protocol. W David Schwaderer. Bran Selic.

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Rex Jones. Machine Learning for the Web. Andrea Isoni. Brett McLaughlin. The New Relational Database Dictionary. Kleppe carefully illuminates good design strategy, showing how to achieve maximum flexibility. Readers will also learn how to create new languages that cooperate well with other languages, and contain references to elements written in those languages. The book contains multiple examples, as well as a running case study, handy summaries, and references, as well as a glossary and abbreviation list. Sidebars, figures, and cartoons present insights and background knowledge designed to help software engineers create successful DSLs as rapidly as possible.

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