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Data Structure and Software Engineering: Challenges and Improvements

✍ Scribed by James L. Antonakos (ed.)


Publisher
Apple Academic Press
Year
2011
Tongue
English
Leaves
348
Category
Library

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✦ Synopsis


Data structure and software engineering is an integral part of computer science. This volume presents new approaches and methods to knowledge sharing, brain mapping, data integration, and data storage. The author describes how to manage an organization’s business process and domain data and presents new software and hardware testing methods. The book introduces a game development framework used as a learning aid in a software engineering at the university level. It also features a review of social software engineering metrics and methods for processing business information. It explains how to use Pegasys to create and manage sequence analysis workflows.

✦ Table of Contents



Content: An Architecture to Support Learning, Awareness, and Transparency in Social Software Engineering --
Comprehending Software Architecture Using a Unified Single-View Visualization --
Determination of Neural Fiber Connections Based on Data Structure Algorithm --
A Preliminary Analysis of Software Engineering Metricsbased Criteria for the Evaluation of Learning Objects Reusability --
Extending Conceptual Schemas with Business Process Information --
Software Test Automation in Practice:Empirical Observations --
A Strategy for Automatic Quality Signing and Verification Processes for Hardware and Software Testing --
A Tester-Assisted Methodology for Test Redundancy Detection --
Automatic Generation of Web Applications from Visual High-Level Functional Web Components --
Challenges and Improvements in Distributed Software Development:A Systematic Review --
Vertical Mining of Frequent Patterns from Uncertain Data --
An Open-Source Representation for 2-DE-Centric Proteomics and Support Infrastructure for Data Storage and Analysis --
Pegasys: Software for Executing and Integrating Analyses of Biological Sequences --
An Application of a Game Development Framework in Higher Education
Abstract:

Presents fresh approaches and methods to knowledge sharing, brain mapping, data integration, data storage, managing an organization's business process and domain data, software and hardware testing Read more...


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