Abstract
Cloud Computing is a technology that provides to customers computing/storage resources as services delivered through the internet. Its main characteristics are its elastic nature and its payment model (pay-as-you-go). In order to run applications in the cloud while using its resources efficiently, and thus reducing their usage costs, one of the requirements related to this type of environment is to perform dynamic configurations of these applications. Nevertheless, to dynamically configure applications determining the utilized resources, additionally to when and where they are used is needed. Workflows allow doing this. As a matter of fact, several works aiming to reduce execution costs in the cloud are based on workflows. Unlike them, the architecture of OO applications explicitly expresses little or no behavioral (temporal) information. Therefore, running an OO application in the cloud requires deploying the whole application, and thus all its used resources need to be allocated during its entire execution time. With the goal of reducing execution costs of OO applications in the cloud, we propose a re-engineering process. The process aims to restructure these applications from OO architectural style to workflow style. However, in this paper, we concentrate only on the first step of the process, which aims to generate a workflow from OO source code.
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Notes
- 1.
A transactional flow specifies the changes occurring in the control flow because of task failure.
- 2.
The procedural knowledge is also known as how to knowledge. For example, cooking recipes are considered as procedural knowledge.
- 3.
Polymorphism need to be dealt with only when using static analysis.
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Selmadji, A., Seriai, AD., Bouziane, H.L., Dony, C. (2019). From Object-Oriented to Workflow: Refactoring of OO Applications into Workflows for an Efficient Resources Management in the Cloud. In: Damiani, E., Spanoudakis, G., Maciaszek, L. (eds) Evaluation of Novel Approaches to Software Engineering. ENASE 2018. Communications in Computer and Information Science, vol 1023. Springer, Cham. https://doi.org/10.1007/978-3-030-22559-9_9
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