The impedance mismatch problem that occurs when relational data is being processed by object-oriented (OO) programs, also occurs when OO programs process RDF data, on the Semantic Web. The impedance mismatch problem s...
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ISBN:
(纸本)9781424489589
The impedance mismatch problem that occurs when relational data is being processed by object-oriented (OO) programs, also occurs when OO programs process RDF data, on the Semantic Web. The impedance mismatch problem stems from the inherent differences between RDF and the data model of OO languages. In this paper, we illustrate a solution to this problem. Essentially, we modify an OO language so that RDF individuals become first-class citizens in the language, and objects of the language become first-class citizens in RDF. Three important benefits that follow from this modification are: (1) it becomes natural to use the language as a persistent programminglanguage, (2) the language supports implicit integration of data from multiple data sources, and (3) SPARQL queries and inference can be applied to objects during the run of a program. This demo presents such a modified programminglanguage, namely ruby on Semantic Web, which is an extension of the ruby programming language. The demo includes a system, where users can run applications, written in ruby on Semantic Web, over multiple data sources. In the demo we run code examples. The effects of the execution on the data sources and on the state of the objects in memory are presented visually, in real time.
Most requirements engineering (RE) research has been conducted in the context of structured and agile software development. Software, however, is increasingly developed in open source software (OSS) forms which have s...
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Most requirements engineering (RE) research has been conducted in the context of structured and agile software development. Software, however, is increasingly developed in open source software (OSS) forms which have several unique characteristics. In this study, we approach OSS RE as a sociotechnical, distributed cognitive process where distributed actors "compute" requirements- i.e., transform requirements-related knowledge into forms that foster a shared understanding of what the software is going to do and how it can be implemented. Such computation takes place through social sharing of knowledge and the use of heterogeneous artifacts. To illustrate the value of this approach, we conduct a case study of a popular OSS project, Rubinius-a runtime environment for the ruby programming language-and identify ways in which cognitive workload associated with RE becomes distributed socially, structurally, and temporally across actors and artifacts. We generalize our observations into an analytic framework of OSS RE, which delineates three stages of requirements computation: excavation, instantiation, and testing-in-the-wild. We show how the distributed, dynamic, and heterogeneous computational structure underlying OSS development builds an effective mechanism for managing requirements. Our study contributes to sorely needed theorizing of appropriate RE processes within highly distributed environments as it identifies and articulates several novel mechanisms that undergird cognitive processes associated with distributed forms of RE.
Navy Supply Systems Command manages a vast inventory of items to meet the fleets requirements. A requisition decision for restocking an item is made, in part, based on the planned minimum safety stock (PMSS) level. Th...
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Navy Supply Systems Command manages a vast inventory of items to meet the fleets requirements. A requisition decision for restocking an item is made, in part, based on the planned minimum safety stock (PMSS) level. The Wholesale Inventory Optimization Model with Enterprise Resource Planning (WIOM-ERP) simulates the fleets requirement demand based on historic data to establish metrics that serve as the basis to recommend the PMSS levels. NAVSUP uses WIOM-ERP to balance its inventory between procurement persistence (avoidance of "churn") and fulfillment of demand (fill rate). WIOM-ERP provides the flexibility for planners to weigh the importance of each metric and shift the balance between churn and fill rate. Decision makers seek insight into the relative tradeoff between churn and fill rate, resulting from changing the weight of each metric. This study applies a high-dimensional statistical design of experiments to simulate different combinations of metric weights for the WIOM-ERP user inputs. The output of WIOM-ERP is recorded for each design point to calculate measures of performance (MOPs) for churn and fill rate. The data are analyzed by developing statistical metamodels for each MOP to determine the impact on the metrics of the factors, their interactions, and the resulting tradeoffs between different combinations of weights.
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