On using Markov decision processes to model integration solutions for disparate resources in software ecosystems

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.The software ecosystem of an enterprise is usually composed of an heterogeneous set of applications, databases, documents, spreadsheets, and so on. Such resources are involved in the enterprise’s daily activities by supporting its business processes. As a consequence of market change and the enterprise evolution, new business processes emerge and the current ones have to be evolved to tackle the new requirements. It is not a surprise that different resources may be required to collaborate in a business process. However, most of these resources were devised without taking into account their integration with the others, i.e., they represent isolated islands of data and functionality. Thus, the goal of an integration solution is to enable the collaboration of different resources without changing them or increasing their coupling. The analysis of integration solutions to predict their behaviour and find possible performance bottlenecks is an important activity that contributes to increase the quality of the delivered solutions. Software engineers usually follow an approach that requires the construction of the integration solution, the execution of the actual integration solution, and the collection of data from this execution in order to analyse and predict their behaviour. This is a costly, risky, and time-consuming approach. This paper discusses the usage of Markov models for formal modelling of integration solutions aiming at enabling the simulation of the conceptual models of integration solutions still in the design phase. By using well-established simulation techniques and tools at an early development stage, this new approach contributes to reduce cost, risk, development time and improve software quality attributes such as robustness, scalability, and maintenance