An Embedded Domain Specific Language to Model, Transform and Quality Assure Business Processes in Business-Driven Development

In Business-Driven Development (BDD), business process models are produced by business analysts. To ensure that the business requirements are satisfied, the IT solution is directly derived through a process of model refinement. If models do not contain all the required technical details or contain errors, the derived implementation would be incorrect and the BDD lifecycle would have to be repeated. In this project we present a functional domain specific language embedded in Haskell, with which: 1) models can rapidly be produced in a concise and abstract manner, 2) enables focus on the specifications rather than the implementation, 3) ensures that all the required details, to generate the executable code, are specified, 4) models can be transformed, analysed and interpreted in various ways, 5) quality assures models by carrying out three types of checks; by Haskell.s type checker, at construction-time and by functions that analyse the soundness of models, 6) enables users to define quality assured composite model transformations

Comics, robots, fashion and programming: outlining the concept of actDresses

This paper concerns the design of physical languages for controlling and programming robotic consumer products. For this purpose we explore basic theories of semiotics represented in the two separate fields of comics and fashion, and how these could be used as resources in the development of new physical languages. Based on these theories, the design concept of actDresses is defined, and supplemented by three example scenarios of how the concept can be used for controlling, programming, and predicting the behaviour of robotic systems

Combining SysML and AADL for the design, validation and implementation of critical systems

The realization of critical systems goes through multiple phases of specification, design, integration, validation, and testing. It starts from high-level sketches down to the final product. Model-Based Design has been acknowledged as a good conveyor to capture these steps. Yet, there is no universal solution to represent all activities. Two candidates are the OMG-based SysML to perform high-level modeling tasks, and the SAE AADL to perform lower-level ones, down to the implementation. The paper shares an experience on the seamless use of SysML and the AADL to model, validate/verify and implement a flight management system

Evaluating Rapid Application Development with Python for Heterogeneous Processor-based FPGAs

As modern FPGAs evolve to include more het- erogeneous processing elements, such as ARM cores, it makes sense to consider these devices as processors first and FPGA accelerators second. As such, the conventional FPGA develop- ment environment must also adapt to support more software- like programming functionality. While high-level synthesis tools can help reduce FPGA development time, there still remains a large expertise gap in order to realize highly performing implementations. At a system-level the skill set necessary to integrate multiple custom IP hardware cores, interconnects, memory interfaces, and now heterogeneous processing elements is complex. Rather than drive FPGA development from the hardware up, we consider the impact of leveraging Python to ac- celerate application development. Python offers highly optimized libraries from an incredibly large developer community, yet is limited to the performance of the hardware system. In this work we evaluate the impact of using PYNQ, a Python development environment for application development on the Xilinx Zynq devices, the performance implications, and bottlenecks associated with it. We compare our results against existing C-based and hand-coded implementations to better understand if Python can be the glue that binds together software and hardware developers.Comment: To appear in 2017 IEEE 25th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM'17

How functional programming mattered

In 1989 when functional programming was still considered a niche topic, Hughes wrote a visionary paper arguing convincingly ‘why functional programming matters’. More than two decades have passed. Has functional programming really mattered? Our answer is a resounding ‘Yes!’. Functional programming is now at the forefront of a new generation of programming technologies, and enjoying increasing popularity and influence. In this paper, we review the impact of functional programming, focusing on how it has changed the way we may construct programs, the way we may verify programs, and fundamentally the way we may think about programs

LEGaTO: first steps towards energy-efficient toolset for heterogeneous computing

LEGaTO is a three-year EU H2020 project which started in December 2017. The LEGaTO project will leverage task-based programming models to provide a software ecosystem for Made-in-Europe heterogeneous hardware composed of CPUs, GPUs, FPGAs and dataflow engines. The aim is to attain one order of magnitude energy savings from the edge to the converged cloud/HPC.Peer ReviewedPostprint (author's final draft

Contract-Based General-Purpose GPU Programming

Using GPUs as general-purpose processors has revolutionized parallel computing by offering, for a large and growing set of algorithms, massive data-parallelization on desktop machines. An obstacle to widespread adoption, however, is the difficulty of programming them and the low-level control of the hardware required to achieve good performance. This paper suggests a programming library, SafeGPU, that aims at striking a balance between programmer productivity and performance, by making GPU data-parallel operations accessible from within a classical object-oriented programming language. The solution is integrated with the design-by-contract approach, which increases confidence in functional program correctness by embedding executable program specifications into the program text. We show that our library leads to modular and maintainable code that is accessible to GPGPU non-experts, while providing performance that is comparable with hand-written CUDA code. Furthermore, runtime contract checking turns out to be feasible, as the contracts can be executed on the GPU