Deriving minimal models for resource utilization

We show how compact Resource Utilization Models (RUMs) can be extracted from concrete overly-detailed models of systems or sub-systems in order to model energy-aware software. Using the Counterexample-Guided Abstraction Refinement (CEGAR) approach, along with model-checking tools, abstract models can be generated that help establish key properties relating to energy consumption. This approach is illustrated by the concrete example of a network manager sub-system. This work is part of an overall design methodology for energy-aware software

Locating Potential Aspect Interference Using Clustering Analysis

Software design continues to evolve from the structured programming paradigm of the 1970s and 1980s and the object-oriented programming (OOP) paradigm of the 1980s and 1990s. The functional decomposition design methodology used in these paradigms reduced the prominence of non-functional requirements, which resulted in scattered and tangled code to address non-functional elements. Aspect-oriented programming (AOP) allowed the removal of crosscutting concerns scattered throughout class code into single modules known as aspects. Aspectization resulted in increased modularity in class code, but introduced new types of problems that did not exist in OOP. One such problem was aspect interference, in which aspects meddled with the data flow or control flow of a program. Research has developed various solutions for detecting and addressing aspect interference using formal design and specification methods, and by programming techniques that specify aspect precedence. Such explicit specifications required practitioners to have a complete understanding of possible aspect interference in an AOP system under development. However, as system size increased, understanding of possible aspect interference could decrease. Therefore, practitioners needed a way to increase their understanding of possible aspect interference within a program. This study used clustering analysis to locate potential aspect interference within an aspect-oriented program under development, using k-means partitional clustering. Vector space models, using two newly defined metrics, interference potential (IP) and interference causality potential (ICP), and an existing metric, coupling on advice execution (CAE), provided input to the clustering algorithms. Resulting clusters were analyzed via an internal strategy using the R-Squared, Dunn, Davies-Bouldin, and SD indexes. The process was evaluated on both a smaller scale AOP system (AspectTetris), and a larger scale AOP system (AJHotDraw). By seeding potential interference problems into these programs and comparing results using visualizations, this study found that clustering analysis provided a viable way for detecting interference problems in aspect-oriented software. The ICP model was best at detecting interference problems, while the IP model produced results that were more sporadic. The CAE clustering models were not effective in pinpointing potential aspect interference problems. This was the first known study to use clustering analysis techniques specifically for locating aspect interference

Specification and Verification of Event Detectors and Responses

Events and aspects that respond to them can and should be defined, specified, and verified in a modular way, as an aid in understanding and guaranteeing the correctness of each on its own. However, finding the appropriate interfaces and abstractions and expressing them precisely is not an easy task. Moreover, formally verifying large models is often unfeasible for existing model-checking tools. We present an abstraction-refinement scheme to verify aspects and to define and correct both aspect and event specifications. This allows considering smaller models and learning the needed event guarantees at each step. In addition, this technique can be used to find sound abstractions to check event reachability. Moreover, the technique is applied for detecting interference in systems where there are responses to complex events and aspects may be activated within the execution of other aspects