System engineering and evolution decision support, Final Progress Report (05/01/1998 - 09-30-2001)

The objective of our effort is to develop a scientific basis for system engineering automation and decision support. This objective addresses the long term goals of increasing the quality of service provided complex systems while reducing development risks, costs, and time. Our work focused on decision support for designing operations of complex modular systems that can include embedded software. Emphasis areas included engineering automation capabilities in the areas of design modifications, design records, reuse, and automatic generation of design representations such as real-time schedules and software.U.S. Army Research OfficeFunding number(s): DSAM 90387, DWAM 80013, DWAM 90215

An Algebra of Design Patterns

In a pattern-oriented software design process, design decisions are made by selecting and instanti- ating appropriate patterns, and composing them together. In our previous work, we enabled these decisions to be formalised by dening a set of operators on patterns with which instantiations and compositions can be represented. In this paper, we investigate the algebraic properties of these operators. We provide and prove a complete set of algebraic laws so that equivalence between pattern expressions can be proven. Furthermore, we dene an always-terminating normalisation of pattern expressions to a canonical form, which is unique modulo equivalence in rst-order logic. By a case study, the pattern-oriented design of an extensible request-handling framework, we demonstrate two practical applications of the algebraic framework. Firstly, we can prove the correctness of a nished design with respect to the design decisions made and the formal specication of the patterns. Secondly, we can even derive the design from these components

Impact estimation: IT priority decisions

Given resource constraints, prioritization is a fundamental process within systems engineering to decide what to implement. However, there is little guidance about this process and existing IT prioritization methods have several problems, including failing to adequately cater for stakeholder value. In response to these issues, this research proposes an extension to an existing prioritization method, Impact Estimation (IE) to create Value Impact Estimation (VIE). VIE extends IE to cater for multiple stakeholder viewpoints and to move towards better capture of explicit stakeholder value. The use of metrics offers VIE the means of expressing stakeholder value that relates directly to real world data and so is informative to stakeholders and decision makers. Having been derived from prioritization factors found in the literature, stakeholder value has been developed into a multi-dimensional, composite concept, associated with other fundamental system concepts: objectives, requirements, designs, increment plans, increment deliverables and system contexts. VIE supports the prioritization process by showing where the stakeholder value resides for the proposed system changes. The prioritization method was proven to work by exposing it to three live projects, which served as case studies to this research. The use of the extended prioritization method was seen as very beneficial. Based on the three case studies, it is possible to say that the method produces two major benefits: the calculation of the stakeholder value to cost ratios (a form of ROI) and the system understanding gained through creating the VIE table