1,721,022 research outputs found
A modeling approach to analyze the impact of error propagation on reliability of component-based systems
No full textWe present a novel approach to the analysis of the reliability of a component-based system that takes into account an important architectural attribute, namely the error propagation probability. This is the probability that an error, arising somewhere in the system, propagates to other components, possibly up to the system output. As we show in the paper, this attribute may heavily affect decisions on crucial architectural choices. Nonetheless, it is often neglected in modeling the reliability of component-based systems. Our modeling approach provides a useful support to the reliability engineering of component-based systems, since it can be used to drive several significant tasks, such as: (i) placing error detection and recovery mechanisms, (ii) focusing the design, implementation and selection efforts on critical components, (iii) devising cost-effective testing strategies. We illustrate the approach on an ATM example system
Analyzing the sensitivity of multi-objective software architecture refactoring to configuration characteristics
No full textContext: Software architecture refactoring can be induced by multiple reasons, such as satisfying new functional requirements or improving non-functional properties. Multi-objective optimization approaches have been widely used in the last few years to introduce automation in the refactoring process, and they have revealed their potential especially when quantifiable attributes are targeted. However, the effectiveness of such approaches can be heavily affected by configuration characteristics of the optimization algorithm, such as the composition of solutions. Objective: In this paper, we analyze the behavior of EASIER, which is an Evolutionary Approach for Software archItecturE Refactoring, while varying its configuration characteristics, with the objective of studying its potential to find near-optimal solutions under different configurations. Method: In particular, we use two different solution space inspection algorithms (i.e., NSGA−II and SPEA2) while varying the genome length and the solution composition. Results: We have conducted our experiments on a specific case study modeled in Æmilia ADL, on which we have shown the ability of EASIER to identify performance-critical elements in the software architecture where refactoring is worth to be applied. Beside this, from the comparison of multi-objective algorithms, NSGA−II has revealed to outperform SPEA2 in most of cases, although the latter one is able to induce more diversity in the proposed solutions. Conclusion: Our results show that the EASIER thoroughly automated process for software architecture refactoring allows to identify configuration contexts of the evolutionary algorithm in which multi-objective optimization more effectively finds near-optimal Pareto solutions
PRIMA-UML: a Performance Validation Incremental Methodology on Early UML Diagrams
No full textAbstractThe development of complex software systems satisfying performance requirements is achievable only spending careful attention to performance goals throughout the lifecycle, and especially from its very beginning. Unified modeling language (UML) is quickly becoming a standard notation for specification and design of software systems. UML offers several diagrams for separating concerns of different system views, and this feature is helpful to derive early performance models that take into account combined data from these diagrams. In this paper, we introduce a methodology Performance Incremental Validation in UML (PRIMA-UML) aimed at generating a queueing network based performance model from UML diagrams that are usually available early in the software lifecycle. PRIMA-UML is incremental in that it combines information extracted from (and annotated into) different UML diagrams to piecewise build the performance model. Besides, this is not a “black box” approach, as the methodology is open to embed information coming from other UML diagrams (possibly in late lifecycle phases) for detailing, refining or domain tailoring the performance model. This work is a contribute to encompass the performance validation task as an integrated activity within the development process of complex systems. We apply the methodology to a quite simple example to show how effective it can be to get early performance insights
From software architecture to analysis models and back: Model-driven refactoring aimed at availability improvement
Full text linkContext: With the ever-increasing evolution of software systems, their architecture is subject to frequent changes due to multiple reasons, such as new requirements. Appropriate architectural changes driven by non-functional requirements are particularly challenging to identify because they concern quantitative analyses that are usually carried out with specific languages and tools. A considerable number of approaches have been proposed in the last decades to derive non-functional analysis models from architectural ones. However, there is an evident lack of automation in the backward path that brings the analysis results back to the software architecture. Objective: In this paper, we propose a model-driven approach to support designers in improving the availability of their software systems through refactoring actions. Method: The proposed framework makes use of bidirectional model transformations to map UML models onto Generalized Stochastic Petri Nets (GSPN) analysis models and vice versa. In particular, after availability analysis, our approach enables the application of model refactoring, possibly based on well-known fault tolerance patterns, aimed at improving the availability of the architectural model. Results: We validated the effectiveness of our approach on an Environmental Control System. Our results show that the approach can generate: (i) an analyzable availability model from a software architecture description, and (ii) valid software architecture models back from availability models. Finally, our results highlight that the application of fault tolerance patterns significantly improves the availability in each considered scenario. Conclusion: The approach integrates bidirectional model transformation and fault tolerance techniques to support the availability-driven refactoring of architectural models. The results of our experiment showed the effectiveness of the approach in improving the software availability of the system
Availability-Driven Architectural Change Propagation Through Bidirectional Model Transformations between UML and Petri Net Models
No full textSoftware architecture is nowadays subject to frequent changes due to multiple reasons, such as evolution induced by new requirements. Architectural changes driven by non-functional requirements are particularly difficult to identify, because they attain quantitative analyses that are usually carried out with specific languages and tools. A considerable number of approaches, based on model transformations, have been proposed in the last decades to derive non-functional models from software architectural descriptions. However, there is a clear lack of automation in the backward path that brings the analysis results back to the software architecture. In this paper we address this problem in the context of software availability. We introduce a bidirectional model transformation between UML State Machines (SM), annotated with availability properties, and Generalized Stochastic Petri Nets (GSPN). Such transformation, implemented in the JTL language, is used both to derive a GSPN-based availability model from a SM-based software architecture and, after the analysis, to propagate back on the SM the changes carried out on the GSPN. We demonstrate the effectiveness of our approach on an Environmental Control System to which we apply well-known fault tolerance patterns aimed at improving its software availability
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