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Automated Function Points

CAST Automated Function Point counts are objective, repeatable, and cost effective. In addition to measuring the size of an application in function points, the CAST Application Intelligence Platform (AIP) also provides precise measures of the changes in the number and complexity of all application components. With this information, IT organizations use CAST to accurately measure software productivity.

Download the CAST Automated Function Points brochure

The Advantage of CAST Automated Function Points

  • Comprehensive: The function point count is based on the entire application no matter how large; thus, there is no need to extrapolate the count from parts of an application.
  • Objective and repeatable: CAST’s automated computable algorithm produces repeatable, consistent results--no human intervention required!
  • Cost-effective: After the initial set up time, the cost of subsequent counts is zero.
  • No documentation needed: CAST Automated Function Points are based on a detailed analysis of the architectural structure of the application. This process does not rely on documentation or application subject matter experts.
  • Consistent comparison: The objectivity, consistency and widespread applicability make CAST Automated Function Points ideal for benchmarking and comparing applications.
  • Essential insight: IT executives get accurate, objective application productivity data to inform funding, resourcing and prioritization decisions.

CAST Makes the Invisible Visible

  • Calculate productivity baseline: CAST AIP establishes a baseline of the number of function points per staff month against which improvement in team productivity can be measured.
  • Track productivity over time: Calculate the number of function points per staff month for every major release of a mission-critical application and compare it with the established baseline. The difference translates into an increase or decrease in productivity.
  • Generate measures of quality and complexity: For all application components and use these additional measures to get a more accurate value for productivity.
  • Identify process inefficiencies: Analyze differences in productivity to highlight points of process inefficiency. Having quality and complexity information in addition to size makes it easier to find and quickly fix the root causes of inefficiency.
  • Measure effectiveness of process improvements: Quantify the effectiveness of process improvement.

Data-driven Guidance to Improve Productivity

  • Map productivity hotspots in your key applications and attain actionable advice to improve productivity
  • Report on team productivity to inform portfolio prioritization, resource allocation and vendor management
  • Measure and communicate improvements in operational efficiency to business partners
  • Improve estimation and resource allocation by measuring productivity based on historical performance 
  • Measure and improve the effectiveness of your operational processes and controls

     

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