rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Source Code Analytics With Roslyn and JavaScript Data Visualization
  name:
    name part: Mukherjee, Sudipta.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: xxu
    date issued: 2016
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XXI, 170 p. 129 illus., 122 illus. in color. online resource.
  abstract: Learn how to build an interactive source code analytics system using Roslyn and JavaScript. This concise 150 page book will help you create and use practical code analysis tools utilizing the new features of Microsoft’s Roslyn compiler to understand the health of your code and identify parts of the code for refactoring. Source code is one of the biggest assets of a software company. However if not maintained well, it can become a big liability. As source code becomes larger. more complex and accessed via the cloud, maintaining code quality becomes even more challenging. The author provides straightforward tools and advice on how to manage code quality in this new environment. Roslyn exposes a set of APIs which allow developers to parse their C# and VB.NET code and drastically lower the barrier to entry for Meta programming in .NET. Roslyn has a dedicated set of APIs for creating custom refactoring for integrating with Visual Studio. This title will show readers how to use Roslyn along with industry standard JavaScript visualization APIs like HighCharts, D3.js etc to create a scalable and highly responsive source code analytics system. .
  table of contents: Chapter 1 Meet Roslyn Syntax -- Chapter 2 Code Quality Metrics -- Chapter 3 Design Quality Metrics -- Chapter 4 Code Performance Metrics -- Chapter 5 Code Mining -- Chapter 6 Code Forensics -- Chapter 7 Code Visualization.
  note: by Sudipta Mukherjee.
  subject:
    topic: Computer science
  subject:
    topic: Computer programming
  subject:
    topic: Software engineering
  subject:
    topic: Programming languages (Electronic computers)
  subject:
    topic: Computer Science
  subject:
    topic: Programming Techniques
  subject:
    topic: Software Engineering
  subject:
    topic: Programming Languages, Compilers, Interpreters
  classification: QA76.6-76.66
  classification: 005.11
  related item:
    title info:
      title: Springer eBooks
  identifier: 9781484219256
  identifier: http://dx.doi.org/10.1007/978-1-4842-1925-6
  record info:
    record creation date: 161221
    record change date: 20161221082247.0
    record identifier: 978-1-4842-1925-6