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This work proposes a quantitative metric to analyze potential reusability of a BPEL (Business Process Execution Language) Process. The approach is based on Description and Logic Mismatch Probability of a BPEL Process that will be reused within potential contexts. The mismatch probabilities have been consolidated to a metric formula for quantifying the probability of potential reuse of BPEL processes. An initial empirical evaluation suggests that the proposed metric properly predict potential reusability of BPEL processes. According to the experiment, there exists a significant statistical correlation between results of the metric and the experts judgements. This indicates a predictive dependency between the proposed metric and potential reusability of BPEL processes as a measuring stick for this phenomena. If future studies ascertain these findings by replicating this experiment, the practical implications of such a metric are early detection of the design flaws and aiding architects to judge various design alternatives.
The role of scalable high-performance workflows and flexible workflow management systems that can support multiple simulations will continue to increase in importance. For example, with the end of Dennard scaling, there is a need to substitute a sing
The main goal of this paper is to discuss how to integrate the possibilities of crowdsourcing platforms with systems supporting workflow to enable the engagement and interaction with business tasks of a wider group of people. Thus, this work is an at
Scientific workflow management systems offer features for composing complex computational pipelines from modular building blocks, for executing the resulting automated workflows, and for recording the provenance of data products resulting from workfl
Infrastructure-as-code (IaC) is a practice to implement continuous deployment by allowing management and provisioning of infrastructure through the definition of machine-readable files and automation around them, rather than physical hardware configu
With the advances in e-Sciences and the growing complexity of scientific analyses, more and more scientists and researchers are relying on workflow systems for process coordination, derivation automation, provenance tracking, and bookkeeping. While w