Reconciling Synthesis and Decomposition: A Composite Approach to Capability Identification

Ravichandar, Ramya; Arthur, James D.; Broadwater, Robert

doi:10.1109/ecbs.2007.61

Cited by 8 publications

(5 citation statements)

References 19 publications

(19 reference statements)

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“…Phase II involves metrics for assessing the schedule/technology trade-offs to arrive at finalized capabilities. These are beyond the scope of this paper but can be found in [10,11].…”

Section: Capabilities Engineeringmentioning

confidence: 97%

“…These entities are designed to exhibit desirable characteristics of high cohesion, low coupling, and balanced abstraction levels-criteria derived from the reconciliation of a synthesis and decomposition approach to capability definition [11]. Using this approach in the early stages of defining the problem domain to produce key elements of the computationally independent models (CIM) can lead to longer-lived architectural components.…”

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confidence: 99%

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Model-based engineering for change-tolerant systems

Bohner

Ravichandar

Arthur

2007

Innovations Syst Softw Eng

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Developing and evolving today's systems are often stymied by the sheer size and complexity of the capabilities being developed and integrated. At one end of the spectrum, we have sophisticated agent-based software with hundreds of thousands of collaborating nodes. These require modeling abstractions relevant to their complex workflow tasks as well as predictable transforms and mappings for the requisite elaborations and refinements that must be accomplished in composing these systems. At the other end of the spectrum, we have ever-increasing capabilities of reconfigurable hardware devices such as field-programmable gate arrays to support the emerging adaptability and flexibility needs of these systems. From a model-based engineering perspective, these challenges are very similar; both must move their abstraction and reuse levels up to meet growing productivity and quality objectives. Model-based engineering and software system variants such as the model-driven architecture (MDA) are increasingly being applied to systems development as the engineering community recognizes the benefits of managing complexity, separating key concerns, and automating transformations from high-level abstract requirements down through the implementation. However, there are challenges when it comes to establishing the correct boundaries for change-tolerant parts of the system. Capabilities engineering (CE) is a promising approach for defining long-lived components of a system to ensure some sense of change tolerance. For innovative initiatives such as the National Aeronautics and Space Administration (NASA)'s autonomous nanotechology swarms (ANTS), the development and subsequent evolution of such systems are of considerable importance as their missions involve complex, collaborative behaviors across distributed, reconfigurable satellites. In this paper, we investigate the intersection of these two technologies as they support the development of complex, change-tolerant systems. We present an effective approach for bounding computationally independent models so that, as they transition to the architecture, capabilitiesbased groupings of components are relevant to the changetolerant properties that must convey in the design solution space. The model-based engineering approach is validated via a fully functional prototype and verified by generating nontrivial multiagent systems and reusing components in subsequent systems. We build off of this research completed on the collaborative agent architecture, discuss the CE approach for the transition to architecture, and then examine how this will be applied in the reconfigurable computing community with the new National Science Foundation Center for High-Performance Reconfigurable Computing. Based on this work and extrapolating from similar efforts, the modelbased approach shows promise to reduce the complexities of software evolution and increase productivity-particularly as the model libraries are populated with canonical components.

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“…Phase II involves metrics for assessing the schedule/technology trade-offs to arrive at finalized capabilities. These are beyond the scope of this paper but can be found in [10,11].…”

Section: Capabilities Engineeringmentioning

confidence: 97%

mentioning

confidence: 99%

Model-based engineering for change-tolerant systems

Bohner

Ravichandar

Arthur

2007

Innovations Syst Softw Eng

Self Cite

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“…Functional decomposition and allocation are key activities which a systems engineer must consider when designing a system. Synthesis and decomposition are specific functions which have an algorithmic formulation that assist in developing capabilities by aggregating system elements and recursively partitioning a system into distinct entities (Ravichandar, Arthur, and Broadwater 2006). Another method of functional decomposition is the Function Analysis Systems Technique (FAST) (Wixson 1999) where a process is followed to identify the functions and components to accomplish a mission.…”

Section: Mission Decompositionmentioning

confidence: 99%

5.2.1 Effecting Quality of Service Across Systems of Systems

Naga

Grimaila

Colombi

et al. 2010

INCOSE International Symp

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Abstract. The ability for diverse communication networks to adapt to changing mission characteristics, such as priority, have been a recognized challenge across Systems of Systems. Within the Department of Defense, mechanisms do not exist to extract dynamic mission features for use in defining Service Level Agreements (SLA) and for use within Quality of Service (QoS) provisioning. These mechanisms, were they to exist, would also serve a wide range of non-defense enterprises. This paper provides background on QoS and SLAs within the current military context. We then offer a research approach to improve on the network-focused, QoS mechanics. Using OpNet, early simulations reproduce the competing cross-mission information environment and serve as the foundation for continued "mission-aware" QoS research.

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“…The algorithm utilizes three principle criteriacohesion, coupling, and abstraction levels-to evaluate the functional abstractions and determine whether they are Capabilities. These criteria are a result of analyzing the FD graph from a top-down and bottom-up perspective to identifying Capabilities [10]. To understand how the algorithm identifies change-tolerant functional abstractions, we first need to discuss the rationale behind these criteria and their corresponding mathematical measures.…”

Section: Formulation Decompositionmentioning

confidence: 99%

Improving change tolerance through Capabilities‐based design: an empirical analysis

Ravichandar

Arthur

Bohner

et al. 2008

J. Softw. Maint. Evol.: Res. Pract.

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We introduce a Capabilities-based approach for constructing large-scale systems such that they are change-tolerant. The inherent complexity of software systems increases their susceptibility to change when subjected to the vagaries of user needs, technology advances, market demands, and other change-inducing factors. Despite the inevitability of change, traditional requirements engineering strives to develop systems based on a fixed solution; a mostly unsuccessful approach as evidenced by the history of system failures. In contrast, we utilize Capabilities-functional abstractions that are neither as amorphous as user needs nor as rigid as system requirements-to architect systems that accommodate change with minimum impact. These entities are designed to exhibit the desirable characteristics of high cohesion, low coupling, and balanced abstraction levels and are generated by a two-phased process called Capabilities Engineering. Phase I mathematically exploits the structural semantics of a function decomposition graph-a representation of user needs-to formulate change-tolerant Capabilities. Phase II optimizes these Capabilities to comply with schedule and technology constraints. In this paper, we present the overall framework of this process and detail the algorithm to identify Capabilities. In addition, we empirically evaluate the change tolerance of Capabilities resulting from Phase I. For this we examine the ripple effect of needs change on a real-world Course Evaluation System based on the original requirements-based design and the corresponding Capabilities-based design. Our experimental results indicate, with statistical significance, that the Capabilities-based design is less impacted by change and thereby improves the change tolerance of the system when subjected to needs volatility.

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Reconciling Synthesis and Decomposition: A Composite Approach to Capability Identification

Cited by 8 publications

References 19 publications

Model-based engineering for change-tolerant systems

Model-based engineering for change-tolerant systems

5.2.1 Effecting Quality of Service Across Systems of Systems

Improving change tolerance through Capabilities‐based design: an empirical analysis

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