Software

About: Software is a research topic. Over the lifetime, 130577 publications have been published within this topic receiving 2028987 citations. The topic is also known as: computer software & computational tool.

Symbolic Data Analysis : Conceptual statistics and data Mining

Abstract: The first book to present a unified account of symbolic data analysis methods in a consistent statistical framework, Symbolic Data Analysis features a substantial number of examples from a range of application areas, including health, the social sciences, economics, and computer science. It includes implementation of the methods described using SODAS software, which has been developed by a team led by Edwin Diday and is freely available on the Web, with an additional chapter that provides a basic guide to the software. It also features exercises at the end of each chapter to help the reader develop their understanding of the methodology, and to enable use of the book as a course text. The book is supported by a website featuring a link to download SODAS software, datasets, solutions to exercises, and additional teaching material.

Review of stereo vision algorithms: From software to hardware

Abstract: Stereo vision, resulting in the knowledge of deep information in a scene, is of great importance in the field of machine vision, robotics and image analysis. In this article, an explicit analysis of the existing stereo matching methods, up to date, is presented. The presented algorithms are discussed in terms of speed, accuracy, coverage, time consumption, and disparity range. Towards the direction of real-time operation, the development of stereo matching algorithms, suitable for efficient hardware implementation is highly desirable. Implementations of stereo matching algorithms in hardware for real-time applications are also discussed in details.

Effectively prioritizing tests in development environment

Abstract: Software testing helps ensure not only that the software under development has been implemented correctly, but also that further development does not break it. If developers introduce new defects into the software, these should be detected as early and inexpensively as possible in the development cycle. To help optimize which tests are run at what points in the design cycle, we have built Echelon, a test prioritization system, which prioritizes the application's given set of tests, based on what changes have been made to the program.Echelon builds on the previous work on test prioritization and proposes a practical binary code based approach that scales well to large systems. Echelon utilizes a binary matching system that can accurately compute the differences at a basic block granularity between two versions of the program in binary form. Echelon utilizes a fast, simple and intuitive heuristic that works well in practice to compute what tests will cover the affected basic blocks in the program. Echelon orders the given tests to maximally cover the affected program so that defects are likely to be found quickly and inexpensively. Although the primary focus in Echelon is on program changes, other criteria can be added in computing the priorities.Echelon is part of a test effectiveness infrastructure that runs under the Windows environment. It is currently being integrated into the Microsoft software development process. Echelon has been tested on large Microsoft product binaries. The results show that Echelon is effective in ordering tests based on changes between two program versions.

Rietveld analysis software for J-PARC

Abstract: A new analysis software suite, Z-Code, is under development for powder diffraction data analyses in the Materials and Life Science Facility (MLF) of the Japan Proton Accelerator Research Complex (J-PARC). This software suite comprises data processing, data analyses, graphical user interface and visualization software. As a part of Z-Code, a Rietveld analysis program for neutron (TOF and angle dispersive) and X-ray data, Z-Rietveld, has been developed. Here we report the basic traits and some significant features of Z-Rietveld.

Machine Vision Algorithms and Applications

Abstract: This first up-to-date textbook for machine vision software provides all the details on the theory and practical use of the relevant algorithms. The first part covers image acquisition, including illumination, lenses, cameras, frame grabbers, and bus systems, while the second deals with the algorithms themselves. This includes data structures, image enhancement and transformations, segmentation, feature extraction, morphology, template matching, stereo reconstruction, and camera calibration. The final part concentrates on applications, and features real-world examples, example code with HALCON, and further exercises. Uniting the latest research results with an industrial approach, this textbook is ideal for students of electrical engineering, physics and informatics, electrical and mechanical engineers, as well as those working in the sensor, automation and optical industries. Free software available with registration code