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生命周期建模语言 (LML) V1.1 英文版
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文件大小: 1mb
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上传时间: 2019-09-05
详细说明： The LML specification’s purpose is to provide a reference for users of the language to understand its goals, concepts and structure and to provide vendors a reference for implementation of the language. The basis for the LML formulation is the classic entity, relationship, and attribute (ERA) meta - meta model. This formulat ion modifies the classical approach slightly by includ ing attributes on relationships, to provide the adverb, as well as the noun (entity), relationship (verb), and attribute (ad jective ) language elements. Since LML was designed to translate to object languages, such as UML/SysML, these language elements correspond to classes (entity), relations (relationship), and properti es (attribute). Current Systems Engineering languages tend to add complexity to already complex problems, thus making it more difficult to communicate the unde rlying issues and develop effective solutions. LML is designed to be a simpler language, both in terms of its ontology and visual expressions. This feature makes it easy to understand by the entire set of lifecycle stakeholders. Such a simplified language many not include all the “bins” for information a particular domain wants, hence, LML is extensible allowing for discipline and domain specific extensions to support the needs of a specific pro ject, organization or customer. The process for extension submission will be detailed on the lifecyclemodeling.org website. For example, UML and SysML use the term Actor to define a part of the system that performs actions . The DoDAF Metamodel 2 uses the word Performer for the same purpose. LML uses the term, Asset, but also allows the user to extend the language by defining Actors or Performers. However, we recommend modelers use the type attribute for Assets instead, as a means to differentiate between these different names. New entities or child entities are recommended only when new attributes and/or relationships are needed. Thus modelers using LML will know what entity to put something in immediately and can adjust the type as needed. We saw this problem in the DoDAF where modelers were often confused by the difference between an operational node and a systems node. When you have two “bins” to put the same kind of information into confusion often results. Further examples of this comparison appear in Appendix A and B. This specification of LML also defines common visualizations for information. For example, the Risk entity has a standard Risk Matrix as its basic diagram. Each entity has these kinds of common visualizations and they need to be as simple as possible to reduce the complexity of the language and make it more understandable by a broader set of stakeh olders. Other visualizations are allowed and encouraged as they aid in expressing the information, which is the real goal of any language visualizations. These can and should be proposed as extensions to the language as well so that others practitioners can benefit from these visualizations. Ontologies provide a set of defined terms and relationships between the terms to capture the information that describes the physical, functional, performance, and programmatic aspects of the system. By system, 1 we mean the entire set of processes, people and things which operate for the benefit of people. Common ways for describing such ontologies is entity, relationship, and attribute (ERA). ERA is often used to define database schemas. LML use s the ERA approach, but extends it by adding attribute s to relationships. The extension reduces the number of relationships needed, just as attributes reduce the number of entities needed. This section defines the ERAs for LML, thus providing the basic definitions of the data type s used to collect information about the system . In addition, we describe how inheritance, extensions, limitations and instantiation can be used by tool developers to remain within the guidelines of this standard. Entity, relationship and attribute have equivalent English language elements: noun, verb, and adjective. With the addition of attributes on the relationship, we also have the equivalent of the adverb. These equivalencies have been provided to aid in understanding the semantics of the language.
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