How to make a bridge between transformation and analysis technologies?

At the Dagstuhl seminar on Transformation Techniques in Software Engineering we had an organized discussion on the intricacies of engineering practicle connections between software analysis and software transformation tools. This abstract summarizes it. This discussion contributes mainly by explicitly focussing on this subject from a general perspective, and providing a first sketch of a domain analysis. First we discuss the solution space in general, and then we compare the merits of two entirely di®erent designs: the monolithic versus the heterogeneous approach

TXL source transformation in practice

Abstract—The TXL source transformation system is widely used in industry and academia for both research and production tasks involving source transformation and software analysis. While it is designed to be accessible to software practitioners, understanding how to use TXL effectively takes time and has a steep learning curve. This tutorial is designed to get you over the initial hump and rapidly move you from a TXL novice to the skills necessary to use it effectively in real applications. Consisting of a combination of one hour lecture presentations followed by one hour practice sessions, this is a hands-on tutorial in which participants quickly learn the basics of how to use TXL effectively in their research or industrial practice. Keywords—TXL, source transformation, platform migration, static analysis, reverse- and re-engineering, rapid prototyping I

Identification of Simulink model antipattern instances using model clone detection

Abstract—One challenge facing the Model-Driven Engineering community is the need for model quality assurance. Specifically, there should be better facilities for analyzing models automat-ically. One measure of quality is the presence or absence of good and bad properties, such as patterns and antipatterns, respectively. We elaborate on and validate our earlier idea of detecting patterns in model-based systems using model clone detection by devising a Simulink antipattern instance detector. We chose Simulink because it is prevalent in industry, has mature model clone detection techniques, and interests our industrial partners. We demonstrate our technique using near-miss cross-clone detection to find instances of Simulink antipatterns derived from the literature in four sets of public Simulink projects. We present our detection results, highlight interesting examples, and discuss potential improvements to our approach. We hope this work provides a first step in helping practitioners improve Simulink model quality and further research in the area. I

A survey of self-management in dynamic software architecture specifications

As dynamic software architecture use becomes more widespread, a variety of formal specification languages have been developed to gain a better understanding of the foundations of this type of software evolutionary change. In this paper we survey 14 formal specification approaches based on graphs, process algebras, logic, and other formalisms. Our survey will evaluate the ability of each approach to specify self-managing systems as well as the ability to address issues regarding expressiveness and scalability. Based on the results of our survey we will provide recommendations on future directions for improving the specification of dynamic software architectures, specifically self-managed architectures

Light-Weight Ontology Alignment using Best-Match Clone Detection

Abstract-Ontologies are a key component of the Semantic Web, providing a common basis for representing and exchanging domain meaning in web documents and resources. Ontology alignment is the problem of relating the elements of two formal ontologies for a semantic domain, in order to identify common concepts and relationships represented using different terminology or language, and thus allow meaningful communication and exchange of documents and resources represented using different ontologies for the same domain. Many algorithms have been proposed for ontology alignment, each with their own strengths and weaknesses. The problem is in many ways similar to nearmiss clone detection: while much of the description of concepts in two ontologies may be similar, there can be differences in structure or vocabulary that make similarity detection challenging. Based on our previous work extending clone detection to modelling languages such as WSDL using contextualization, in this work we apply near-miss clone detection to the problem of ontology alignment, and use the new notion of "best-match" clone detection to achieve results similar to many existing ontology alignment algorithms when applied to standard benchmarks

Analysis and clustering of model clones: An automotive industrial experience

Abstract—In this paper we present our early experience analyzing subsystem similarity in industrial automotive models. We apply our model clone detection tool, SIMONE, to identify identical and near-miss Simulink subsystem clones and cluster them into classes based on clone size and similarity threshold. We then analyze clone detection results using graph visualizations generated by the SIMGraph, a SIMONE extension, to identify subsystem patterns. SIMGraph provides us and our industrial partners with new interesting and useful insights that improves our understanding of the analyzed models and suggests better ways to maintain them. I

Towards a Taxonomy for Simulink Model Mutations

Abstract—A relatively new and important branch of Mutation Analysis involves model mutations. In our attempts to realize model-clone detector testing, we found that there was little mutation research on Simulink, which is a fairly prevalent modeling language, especially in embedded domains. Because Simulink model mutations are the crux of our model-clone detector testing framework, we want to ensure that we are selecting the appropriate mutations. In this paper, we propose a taxonomy of Simulink model mutations, which is based on our experiences thus far with Simulink, that aims to inject model clones of various types and is fairly representative of realistic Simulink edit operations. We organize the mutations by categories based on the types of model clones they will inject, and further break them down into mutation classes. For each class, we define the characteristics of mutation operators belonging to that class and demonstrate an example operator. Lastly, in an attempt to validate our taxonomy, we perform a case study on multiple versions of three Simulink projects, including an industrial project, to ascertain if the actual subsystem edit operations observed across versions can be classified using our taxonomy and present any interesting cases. While we developed the taxonomy with the specific goal of facilitating and guiding the injection of mutants for model clones, we believe it is fairly general and a solid foundation for future Simulink model mutation work. I

Similarity in Programs

An overview of the concept of program similarity is presented. It divides similarity into two types - syntactic and semantic - and provides a review of eight categories of methods that may be used to measure program similarity. A summary of some applications of these methods is included. The paper is intended to be a starting point for a more comprehensive analysis of the subject of similarity in programs, which is critical to understand if progress is to be made in fields such as clone detection

SimNav: Simulink navigation of model clone classes

SimNav is a GUI designed for displaying and navigating clone classes of Simulink models detected by the model clone detector Simone. As an embedded Simulink interface tool, SimNav allows model developers to explore detected clones directly in their own model development environment rather than a separate research tool interface. SimNav allows users to open selected models for side-by-side comparison, in order to visually explore clone classes and view the differences in the clone instances, as well as to explore the context in which the clones exist. This tool paper describes the motivation, implementation, and use cases for SimNav