From FPGA to ASIC: A RISC-V processor experience

This work document a correct design flow using these tools in the Lagarto RISC- V Processor and the RTL design considerations that must be taken into account, to move from a design for FPGA to design for ASIC

Improving NDT with Automatic Test Case Generation

The model-driven development defi nes the software development process as a set of iterations to create models and a set of transformations to obtain new models. From this point of view, this paper presents the enhancement of a model- driven approach, called navigational development techniques (NDT), by means of new models and transformations in order to generate test cases. It also states some conclusions from the research work and practical cases in which this approach was used.Ministerio de Ciencia e Innovación TIN2010-20057-C03-02Ministerio de Ciencia e Innovación TIN 2010-12312-

Practical Application Of Uml Activity Diagrams For The Generation Of Test Cases

Software testing and debugging represents around one third of total effort in development projects. Different factors which have influence on poor practices of testing have been identified through specific surveys. Amongst several, one of the most important is the lack of efficient methods to exploit development models for generating test cases. This paper presents a new method for automatically generating a complete set of functional test cases from UML activity diagrams complementing specification of use cases. Test cases are prioritized according to software risk information. Results from experiences with more than 70 software professionals/experts validate benefits of the method. Participants also confirm its interest and effectiveness for testing needs of industry

Web Data Extraction, Applications and Techniques: A Survey

Web Data Extraction is an important problem that has been studied by means of different scientific tools and in a broad range of applications. Many approaches to extracting data from the Web have been designed to solve specific problems and operate in ad-hoc domains. Other approaches, instead, heavily reuse techniques and algorithms developed in the field of Information Extraction. This survey aims at providing a structured and comprehensive overview of the literature in the field of Web Data Extraction. We provided a simple classification framework in which existing Web Data Extraction applications are grouped into two main classes, namely applications at the Enterprise level and at the Social Web level. At the Enterprise level, Web Data Extraction techniques emerge as a key tool to perform data analysis in Business and Competitive Intelligence systems as well as for business process re-engineering. At the Social Web level, Web Data Extraction techniques allow to gather a large amount of structured data continuously generated and disseminated by Web 2.0, Social Media and Online Social Network users and this offers unprecedented opportunities to analyze human behavior at a very large scale. We discuss also the potential of cross-fertilization, i.e., on the possibility of re-using Web Data Extraction techniques originally designed to work in a given domain, in other domains.Comment: Knowledge-based System