Abstract
Model-driven engineering approaches aim at avoiding productivity, model quality and model maintenance problems that arise when models are used for documentation only, by generating executable applications from models. However, in many cases, the level of detail of the models needed to generate complete applications is too much or only effective for specific domains. For those cases where it is not practical to build complete models and generate complete applications from them, we propose a lightweight approach, applicable at different levels (unit, integration and system testing), that combines partial application generation from structural models with test generation from partial behavioral models. To demonstrate the approach, we developed a plug-in that adds to the code generation capabilities of an existing UML modeling tool, the capability of generating executable tests from sequence diagrams acting also as parameterized test scenarios, including some novel features as compared to existing model-based testing tools.

Abstract
With the restructuring of the energy sector in industrialized countries there is an increased complexity in market players' interactions along with emerging problems and new issues to be addressed. Decision support tools that facilitate the study and understanding of these markets are extremely useful to provide players with competitive advantage. In this context arises MASCEM, a multi-agent simulator for competitive electricity markets. It is essential to reinforce MASCEM with the ability to recreate electricity markets reality in the fullest possible extent, making it able to simulate as many types of markets models and players as possible. This paper presents the development of the Balancing Market in MASCEM. A key module to the study of competitive electricity markets, as it has well defined and distinct characteristics previously implemented.

Abstract
VLIW architectures are seeing increased deployment in a number of hostile environments. In addition, softcore VLIW architectures, which allow for run-time customization of the VLIW datapath, are becoming viable for a number of safety-critical applications. As error and failure rates rise, these applications elicit a need for automated and resilient architecture configuration tools. To mitigate these issues, this paper presents a Resiliency-aware Scheduling approach to the configuration of a custom VLIW architecture, providing computational resilience via software duplication. The automated RaS tool determines the optimal set of resources needed to provide a given level of resilience for a reconfigurable softcore VLIW architecture. For a sample case study, based on a common physics code kernel, the RaS approach is compared to traditional hardware (TMR) and software (source-level code replication) approaches. Results show a Resiliency-aware Scheduling-generated architecture configuration can potentially require up to 50% fewer functional units when compared to a TMR-hardened machine of similar performance, and can potentially improve performance by up to 40% over source-level software approaches. © 2012 IEEE.

Abstract
In game development there is often the need to generate realistic urban environments, i.e. 3D virtual environments that replicate existing urban areas. However, modeling such spaces using traditional techniques is both too slow and too expensive. A good solution is the use of procedural modeling techniques to automate the process. However these techniques require large amounts of geospatial data, which are usually stored in Geographic Information Systems (GIS). This paper presents a pipeline for the integration of both geometric and semantic data from GIS data sources into procedural modeling techniques used for the generation of 3D virtual urban environments. GIS data can already be used in procedural modeling tools but these do not provide an easy and uniform way to incorporate semantic information from different data sources. To solve this problem, the proposed pipeline is capable of transforming semantic and geometric information from different sources into 3D environments that replicate specific urban areas.

Abstract
Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM is a multi-agent electricity market simulator to model market players and simulate their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. MASCEM is integrated with ALBidS, a system that provides several dynamic strategies for agents' behavior. This paper presents a method that aims at enhancing ALBidS competence in endowing market players with adequate strategic bidding capabilities, allowing them to obtain the higher possible gains out of the market. This method uses a reinforcement learning algorithm to learn from experience how to choose the best from a set of possible actions. These actions are defined accordingly to the most probable points of bidding success. With the purpose of accelerating the convergence process, a simulated annealing based algorithm is included.

Abstract
The number of configurable systems deployed in hostile environments continues to rise. This, along with decreasing geometries and lower operating voltages leads to an expected increase in transient errors. This paper presents Resiliency-aware Scheduling, a novel approach to resource allocation for hardening computations on configurable systems. Using modular and replicated functional units called hybrid TMR that exploit a computation's Intrinsic Resiliency, our results show that for designs with similar performance, RaS exhibits a 60% area savings over a traditional TMR configuration with the same operation coverage. © 2012 IEEE.