Technical Report: System Qualities Ontology, Tradespace and Affordability (SQOTA) Project – Phase 4

Report Number: Technical Report SERC-2016-TR-101

Report Name: System Qualities Ontology, Tradespace and  Affordability (SQOTA) Project – Phase 4

Publication Date:  February 10, 2016 

Project: Tradespace and Affordability


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Executive Summary

This task was proposed and established as a result of a pair of 2012 workshops sponsored by the DoD Engineered Resilient Systems technology priority area and by the SERC.  The workshops focused on how best to strengthen DoD’s capabilities in dealing with its systems’ non-functional requirements, often also called system qualities, properties, levels of service, and –ilities.  The term –ilities was often used during the workshops, and became the title of the resulting SERC research task: “ilities Tradespace and Affordability Project (iTAP).”  As the project progressed, the term “ilities” often became a source of confusion, as in “Do your results include considerations of safety, security, resilience, etc., which don’t have “ility” in their names?”  Also, as our ontology, methods, processes, and tools became of interest across the DoD and across international and standards communities, we found that the term “System Qualities” was most often used.  As a result, we are changing the name of the project to “System Qualities Ontology, Tradespace, and Affordability (SQOTA).”  Some of this year’s university reports still refer to the project as “iTAP.”

Phase 4 Objectives, Tasks, and Results

Task 1. SQ Foundations and Frameworks

Rather than attempt a breadth-first elaboration of the 176 SQ Synergies and Conflicts strategies in the 7×7 matrix, including its ontology elements of Referents, States, Processes, and Relations for each strategy, the USC ontology-based research did a depth-first research effort on a particular SQ that touches all of the four major SQ categories. This SQ is Maintainability. It clearly drives Life Cycle Efficiency, as typically at least 75% of a system’s Total Cost of Ownership is spent on operations and maintenance. It is one of two means for achieving Changeability, involving external change vs. the internal change accomplished by Adaptability. It is clearly key to Dependability, as Maintainability in terms of Mean Time to Repair (MTTR) is the key relation between Reliability in terms of Mean Time Between Failures (MTBF) and Availability in the relation Availability = MTBF / (MTBF + MTTR). And the key systems aspects being depended-upon are primarily the components of Mission Effectiveness.

This depth-first approach thus provided insights on the overall Product Quality ontology structure without having to consider all of the 176 strategies in depth. The insights resulted in changes to the SQ terminology, as shown in the main description of the Phase 4 Results. Examples are changing Resource Utilization to Life Cycle Efficiency, to be more compatible with the Better Buying Power terminology, and changing Flexibility to Changeability, to be better aligned with the MIT Quality In Use ontology structure.

The MIT Quality In Use ontology structure was refined to address further semantic aspects, and requirements for a translation layer to facilitate its use were developed, as elaborated in the main Phase 4 results section. Similarly, the U. Virginia Phase 4 research on formalizing both the MIT and USC ontologies is elaborated in the main Phase 4 results section. An initial semantic diagram relating the USC and MIT terms and relationships is also presented in the main Phase 4 results section.

Task 2. SQ-Oriented tool demos and extension plans.

The USC depth-first exploration of Maintainability identified the need for a better balance of attention during the system acquisition phase between optimizing on system acquisition cost effectiveness and optimizing on system life-cycle cost-effectiveness, particularly for software, due to the major differences between software and software logistical aspects. This led to the development of a proposed framework of Maintainability Readiness Levels for Software Intensive Systems. Again, details are provided in in the main Phase 4 results section.

Other Task 2 Phase 4 Objectives, Tasks and Results summaries will be provided later.

Task 3: Next-Generation, Full-Coverage Cost Estimation Model Ensembles.

The Task 3 Phase 4 Objectives, Tasks and Results summaries will be provided later.

 Additional Research Team:

  • Ms. Celia Chen

Researchers

Collaborators