Run-Time Monitoring-Based Evaluation and Communication Integrity Validation of Software Architectures

Abstract

Architecture descriptions greatly contribute to the understanding, evaluation and evolution of software but despite this, up-to-date software architecture views are rarely available. Typically only initial descriptions of the static view are created but during the development and evolution process the software drifts away from its description. Methods and corresponding tool support for reconstructing and evaluating the current architecture views have been developed and proposed, but they usually address the reconstruction of static and dynamic views separately. Especially the dynamic views are usually bloated with low-level information (e.g. object interactions) making the understanding and evaluation of the behavior very intricate. To overcome this, we presented ARAMIS, a general architecture for building toolbased approaches that support the architecture-centric evolution and evaluation of software systems with a strong focus on their behavior. This work presents ARAMIS-CICE, an instantiation of ARAMIS. Its goal is to automatically test if the run-time interactions between architecture units match the architecture description. Furthermore, ARAMIS-CICE characterizes the intercepted behavior using two newly-defined architecture metrics. We present the fundamental concepts of ARAMIS-CICE: its meta-model, metrics and implementation. We then discuss the results of a two-folded evaluation. The evaluation shows very promising results.

Evolution of Object Oriented Coupling Metrics: A Sampling of 25 Years of Research

“…Most of the tools for dynamic analysis, no matter if industrial or academic, ignore these metrics (e.g., Kieker 12 ). Those who do regard them, either define new ones and/or use them fust for system comprehension (e.g., ARAMIS [40]), but do not offer any impact analysis of the results.…”

Towards an Architecture Quality Index for the Behavior of Software Systems

“…Further on, the higher the benchmarking level, the more attributes are considered and the harder it is, to achieve the values of the anomalies thresholds (see Figure 2). In this section we will exemplify the construction of an architecture quality index in the context of the ARAMIS-CICE (the Architecture Analysis and Monitoring Infrastructure for Architectural Communication Integrity Checking and Evaluation) infrastructure presented in [2]. ARAMIS-CICE is an instantiation of ARAMIS, a general architecture for building tool-based approaches that support the architecturecentric evolution and evaluation of software systems with a strong focus on their behavior.…”

“…The meta-model is explained in detail in [2] and thus we limit ourselves to explaining only its main characteristics.…”

“…The Integrity Validator validates the mapped communication against its governing communication rules. The mapped and validated data is then resent to the AIBR and eventually rerouted to a Metrics Processor, that computes for each of the involved architecture units the values of two metrics used to characterize the current unit's behavior [2]. Note that the metrics computed within ARAMIS-CICE are merely offering a characterization of the behavior of the units (low vs. medium vs. high behavioral cohesion and coupling), but are not suitable for evaluating the quality of the analyzed behavior.…”

“…We consider that a similar index could be useful for assessing and comparing software architectures as well. The goal of this paper is to explore the creation of an architecture quality index for the context of our research project ARAMIS [2].…”