TestingDocs.com
Software Testing website
  • Automation
    • Selenium
    • JBehave Framework
  • Tutorials
    • MySQL Tutorials
    • Testlink
    • Maven
    • Git
  • IDEs
    • IntelliJ IDEA
    • Eclipse
  • Flowcharts
    • Flowgorithm
    • Raptor
  • About

Software Testing

Error Removal Effectiveness Metrics

Overview

In this tutorial, we will discuss two important metrics for error removal effectiveness. Provided below are sample error distribution and sample weights of the different classifications of the errors.

  • DERE
  • DWERE

Let’s assume a Sample hypothetical project called  TestingDocs with 325 KLOC and the development effort hours of 540 man-hours. The Error distribution is given below.

Errors detected Distribution: Table 1

Errors Code Testing Development

Sample Error Weights: Table 2

The sample defect weights in the project are as below. There are classified into three categories called

Simple, Average, and Complex.

Sample Defect Weights

 

DERE(Development Errors Removal Effectiveness)

DERE =\huge \frac{NDE}{(NDE + NYF)}

 

NDE = Number of Design & Development errors

NYF = Number of software failures in 1 year of Maintenance

Let’s calculate the metric for the Sample project based on the given data. Lookup the above table 1 for the number of design and development errors detected during those phases.

NDE = \huge 15

NYF = Number of software failures in 1 year of Maintenance = \huge 18

DERE = \huge \frac{15}{(15 + 18)}

 

= \huge \frac{15}{33}   =  \huge 0.45

 

DERE DWERE Software Metrics

DWERE(Development  Weighted Errors Removal Effectiveness)

 

DWERE = \huge \frac{WDE}{(WDE + WYF)}

 

WDE=The Weighted Development&Design Errors.

WYF = The Weighted number of software failures in 1 year of Maintenance.

Lookup both the tables 1 and 2 for the errors in the classifications and multiply with the corresponding defect weights to get the weighted score.

WDE = \huge 6*(2) + 7*(5) + 2*(10) = 12 + 35 + 20

= \huge 67

 

WYF = \huge 9*(2) + 6*(5) + 3*(10) = 18 + 30 + 30

= \huge 78

 

DWERE = \huge \frac{67}{(67 + 78)}

 

= \huge \frac{67}{145}

 

= \huge 0.46

 

Error Density Metrics

https://www.testingdocs.com/error-density-metrics/

Related Posts

PuTTY Tool UI

Software Testing /

Useful Tools for Software Testers

Errors Code Testing Development

Software Testing /

Error Density Metrics

RACI Chart

Software Testing /

RACI Chart

Android Calculator Icon

Software Testing /

Android Calculator Test Cases

Software Testing /

Open source eCommerce Platforms

‹ RACI Chart› Error Density Metrics

Recent Posts

  • MS Access Data Types
  • Install RAPTOR Avalonia on CentOS
  • Download RAPTOR Avalonia Edition on Windows
  • npm doctor command
  • Build & Run CLion Project
  • Create New CLion C Project on Windows
  • Configure CLion Toolchains on Windows
  • Launch CLion IDE on Windows
  • Activate CLion IDE
  • CLion IDE for C/C++ Development

Back to Top

Links

  • Contact
  • Privacy Policy
  • Cookie Policy

www.TestingDocs.com

Go to mobile version