Automated Model-Based Configuration of Enterprise Java Applications

Abstract

Abstract-The decentralized process of configuring enterprise applications is complex and error-prone, involving multiple participants/roles and numerous configuration changes across multiple files, application server settings, and database decisions. This paper describes an approach to automated enterprise application configuration that uses a feature model, executes a series of probes to verify configuration properties, formalizes feature selection as a constraint satisfaction problem, and applies constraint logic programming techniques to derive a correct application configuration. To validate the approach, we developed a configuration engine, called Fresh, for enterprise Java applications and conducted experiments to measure how effectively Fresh can configure the canonical Java Pet Store application. Our results show that Fresh reduces the number of lines of hand written XML code by up to 92% and the total number of configuration steps by up to 72%.

Using Filtered Cartesian Flattening and Microrebooting to Build Enterprise Applications with Self-adaptive Healing

“…After the new application configuration and service composition is derived, Refresh invokes the container's shutdown sequence to properly release resources, abort transactions and perform other critical activities. The new configuration is injected into the container through programmatic calls or by regenerating the application's configuration files (White et al, 2007a). After the configuration is injected into the container, the application is launched in the new configuration without the failed service, as shown in Figure 9.…”

“…To derive a new configuration of the application that does not include the failed feature, Refresh transforms the feature selection problem into a constraint satisfaction problem (CSP) using techniques that have been developed by us an others in prior work (Benavides et al, 2005, White, et al, 2007a, 2007b. Once the feature selection problem is transformed into a CSP, a high-performance general purpose constraint solver, such as the Java Choco (Benavides et al, 2007) solver, is used to derive a new set of features/configuration for the application.…”

“…Prior work (Benavides et al, 2005(Benavides et al, , 2007White et al, 2007a) provides extensive details on the process for transforming a feature selection problem into a CSP (Cohen, 1990), which is the input format of a constraint solver and deriving a feature selection. We briefly cover this mapping below.…”

Model-Driven Product-Line Architectures for Mobile Devices

“…In previous work (White et al [2007a]), we delineated a process for incorporating global resource constraints into the feature selection process. Our formulation of global resource constraints has been incorporated into infrastructure-driven product variant configuration.…”

“…This technique provides an intuitive mechanism for describing variability and has been applied across a large number of domains, including automotive construction, boilers for nuclear reactors, and mobile devices. Formal mechanisms also exist to translate feature models and the selection of product variants into Constraint Satisfaction Problems (CSPs) (Benavides et al [2005], White et al [2007a]). …”