Generic Pipelined Processor Modeling and High Performance Cycle-Accurate Simulator Generation

Detailed modeling of processors and high performance cycle-accurate simulators are essential for today's hardware and software design. These problems are challenging enough by themselves and have seen many previous research efforts. Addressing both simultaneously is even more challenging, with many existing approaches focusing on one over another. In this paper, we propose the Reduced Colored Petri Net (RCPN) model that has two advantages: first, it offers a very simple and intuitive way of modeling pipelined processors; second, it can generate high performance cycle-accurate simulators. RCPN benefits from all the useful features of Colored Petri Nets without suffering from their exponential growth in complexity. RCPN processor models are very intuitive since they are a mirror image of the processor pipeline block diagram. Furthermore, in our experiments on the generated cycle-accurate simulators for XScale and StrongArm processor models, we achieved an order of magnitude (~15 times) speedup over the popular SimpleScalar ARM simulator.Comment: Submitted on behalf of EDAA (http://www.edaa.com/

Colored model based testing for software product lines (CMBT-SWPL)

Over the last decade, the software product line domain has emerged as one of the mostpromising software development paradigms. The main benefits of a software product lineapproach are improvements in productivity, time to market, product quality, and customersatisfaction.Therefore, one topic that needs greater emphasis is testing of software product lines toachieve the required software quality assurance. Our concern is how to test a softwareproduct line as early as possible in order to detect errors, because the cost of error detectedIn early phases is much less compared to the cost of errors when detected later.The method suggested in this thesis is a model-based, reuse-oriented test technique calledColored Model Based Testing for Software Product Lines (CMBT-SWPL). CMBT-SWPLis a requirements-based approach for efficiently generating tests for products in a soft-ware product line. This testing approach is used for validation and verification of productlines. It is a novel approach to test product lines using a Colored State Chart (CSC), whichconsiders variability early in the product line development process. More precisely, the vari-ability will be introduced in the main components of the CSC. Accordingly, the variabilityis preserved in test cases, as they are generated from colored test models automatically.During domain engineering, the CSC is derived from the feature model. By coloring theState Chart, the behavior of several product line variants can be modeled simultaneouslyin a single diagram and thus address product line variability early. The CSC representsthe test model, from which test cases using statistical testing are derived.During application engineering, these colored test models are customized for a specificapplication of the product line. At the end of this test process, the test cases are generatedagain using statistical testing, executed and the test results are ready for evaluation. Inxaddition, the CSC will be transformed to a Colored Petri Net (CPN) for verification andsimulation purposes.The main gains of applying the CMBT-SWPL method are early detection of defects inrequirements, such as ambiguities incompleteness and redundancy which is then reflectedin saving the test effort, time, development and maintenance costs

Translating UML State Machines to Coloured Petri Nets Using Acceleo: A Report

UML state machines are widely used to specify dynamic systems behaviours. However its semantics is described informally, thus preventing the application of model checking techniques that could guarantee the system safety. In a former work, we proposed a formalisation of non-concurrent UML state machines using coloured Petri nets, so as to allow for formal verification. In this paper, we report our experience to implement this translation in an automated manner using the model-to-text transformation tool Acceleo. Whereas Acceleo provides interesting features that facilitated our translation process, it also suffers from limitations uneasy to overcome.Comment: In Proceedings ESSS 2014, arXiv:1405.055

A group learning management method for intelligent tutoring systems

In this paper we propose a group management specification and execution method that seeks a compromise between simple course design and complex adaptive group interaction. This is achieved through an authoring method that proposes predefined scenarios to the author. These scenarios already include complex learning interaction protocols in which student and group models use and update are automatically included. The method adopts ontologies to represent domain and student models, and object Petri nets to specify the group interaction protocols. During execution, the method is supported by a multi-agent architecture

A comparative analysis of business process modelling techniques

Business process modelling is an increasingly popular research area for both organisations and academia due to its usefulness in facilitating human understanding and communication. Several modelling techniques have been proposed and used to capture the characteristics of business processes. However, available techniques view business processes from different perspectives and have different features and capabilities. Furthermore, to date limited guidelines exist for selecting appropriate modelling techniques based on the characteristics of the problem and its requirements. This paper presents a comparative analysis of some popular business process modelling techniques. The comparative framework is based on five criteria: flexibility, ease of use, understandability, simulation support and scope. The study highlights some of the major paradigmatic differences between the techniques. The proposed framework can serve as the basis for evaluating further modelling techniques and generating selection procedures

Assessing the Risk of an Adaptation using Prior Compliance Verification

Autonomous systems must respond to large amounts of streaming information. They also must comply with critical properties to maintain behavior guarantees. Compliance is especially important when a system self-adapts to perform a repair, improve performance, or modify decisions. There remain significant challenges assessing the risk of adaptations that are dynamically configured at runtime with respect to critical property compliance. Assuming compliance verification was performed for the originally deployed system, the proof process holds valuable meta-data about the variables and conditions that impact reusing the proof on the adapted system. We express this meta-data as a verification workflow using Colored Petri Nets. As dynamic adaptations are configured, the Petri Nets produce alert tokens suggesting the potential proof reuse impact of an adaptation. Alert tokens hold risk values for use in a utility function to determine the least risky adaptations. We illustrate the modeling and risk assessment using a case study