This paper describes rich definitions and shows their value in providing clear, precisely-enough, contextual definitions of customer terminology.

Competitive Engineering: A Handbook For Systems Engineering, Requirements Engineering, And Software Engineering Using Planguage

Using Rich Definitions to Improve Customer Communication

I believe that most current requirement specifications lack clarity, and are very poor in their supporting information. We need to make requirement specifications ‘work harder’ by adding more ‘background’ to the requirements By ‘background’ I mean information related to the requirement that is not the core requirement itself. The background information I am referring to includes: prioritization (expressed by such means as ‘Justification’), risk management (expressed using such means as ‘Assumptions’), change management (for example, the integration requirements), and quality control (for example, the testability requirements).



To improve requirement specification, I have developed a requirement specification language, as a subset of my planning language, ‘Planguage‘. This language has developed by practical need, in international industry over three decades, and is supplemented here with some recent ideas. This paper will give an overview of the conceptual basis and some sample detail.

8.1.1 The Use of Planguage to Improve Requirement Specifications

Adopting AI as a technology that solves a particular problem (i.e., meets an architectural driver) is a significant architectural decision. Existing techniques for adequacy assessment of architectural decisions often fail to predict effects of adopting complex technologies such is AI. In this paper, we argue that the reason for this is that they fail to capture the level of knowledge that architects have about a complex technology that they aim to adopt, making the discussion about it difficult and adequacy check prone to mistakes. To solve these issues, we introduce an approach that instructs architects to decompose complex drivers for adopting new technologies according to properties of the technology, and to explicitly assess knowledge that architects have about each of those properties. In order to do so, we present a template that explicitly captures the level of knowledge that architects have about important AI properties, which serve as new requirements exposing the influence of adopting AI on software system. Through evaluation, we have demonstrated that our approach successfully complements existing adequacy assessment techniques and is able to expose influences of adopting new complex technologies on underlying software architecture.

Knowledge-based Adequacy assessment Approach to support AI adoption

In order to properly support the systems engineering process, the systems engineering profession needs to consciously adopt a more productive view of systems architecture. Many existing definitions of systems architecture are too narrow: they focus too much on ‘structure.’ The focus needs to be shifted to the impact on requirements.

4.4.4 Systems Architecture: A View Based on Multiple Impacts

This paper aims to propose and demonstrate a method for assessing cost and the value for Stakeholders along complex products lifecycle. The method includes the product analysis to identify all the lifecycle phases and respective activities, the stakeholder mapping, classification and selection, relationship to the product and, at final, the data weighing to give a normalized view of cost and value perceived by the stakeholders during the product entire lifecycle. The method runs alongside the early product development process showing how cost and value may vary according to the product lifecycle. Metrics derived in the method can be used to manage the stakeholders to aim get successes during the life of a complex product. The method is demonstrated on the SARA suborbital system developed by the Institute of Aeronautics and Space and the Brazilian industry, in Sao Jose dos Campos, SP, Brazil. SARA is a small Brazilian satellite for microgravity experiments with reentry in atmosphere. This project is adequate for demonstrating the method due the complexity involved. Main stakeholders in the project are scientists, systems architects, industry, funding agencies. In an article presented in the 2008 International Aeronautical Congress the initial studies were shown and now the method is presented in its final version. 

background

/pdf/complex-product-development-approach-considering-value-and-4gag8pt386.pdf

Competitive Engineering: A Handbook For Systems Engineering, Requirements Engineering, And Software Engineering Using Planguage

Citations

Using Rich Definitions to Improve Customer Communication

8.1.1 The Use of Planguage to Improve Requirement Specifications

Knowledge-based Adequacy assessment Approach to support AI adoption

4.4.4 Systems Architecture: A View Based on Multiple Impacts

Complex Product Development Approach Considering Value and Cost for the Stakeholders Along the Product Lifecycle

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