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Tuesday, July 10, 2012

What Tools are used for code coverage analysis?


Code coverage analysis is quite an essential process that makes up the complete and efficient software testing process. 
This analyzation consists of the following three basic activities:
  1. Checking out for the areas of the software system or application that have not been exercised by the set of tests that have been performed so far.
  2. Creation of the additional test cases so that the code coverage can be increased.
  3. Determination of the quantitative measure for the code coverage which some what provides an indirect measure of the quality of the software system and application.
Apart from this, there is one more optional aspect of the code coverage analysis which is that it helps in the identification of the redundant test cases that add to the measure of the code coverage but do not merely increase it.
In this article we have discussed about the tools that make this whole process of code coverage analyzation quite easy.

Tools Used for Code Coverage Analysis


- The code coverage analyzation is quite an effort and time consuming process and therefore is nowadays automated using tools like code coverage analyzer. 
- But a code coverage analyzer cannot be used always like in situations when the tests have to be run through the release candidate.
- For different languages, there are many different and vivid tools are available for code coverage analysis.

  1. For C++ and C programming languages:
a)  Tcov
b)  Bulls eye coverage
c)  Gcov
d)  LDRA test bed
e)  NuMega True Coverage
f)   Tessy
g)  Trucov
h)  Froglogic’s squish coco
i)   Parasoft C++ soft
j)   Test well CTC++
k)  McCabe IQ
l)   Insure++
m)Cantata

  1. Tools for C#:
a)  Mc Cabe IQ
b)  Jet brains dot cover
c)  Ncover
d)  Visual studio 2010
e)  Parasoft Dottest
f)   Test driven.NET
g)  Kalistick
h)  Dev partner

  1. Tools for Java:
a)  McCabe IQ
b)  Clover
c)  EMMA
d)  Kalistick
e)  JaCoCo
f)   JMockit coverage
g)  Code coverage
h)  LDRA test bed
i)    Jtest
j)   Den partner
k)  Cobertura

  1. Tools for Java Script:
a) Mc Cabe IQ
b) JS coverage
c) Code coverage
d) Script cover
e) Coveraje

  1. Tools for Perl:
a) Mc Cabe IQ
b)  Devel cover

  1. Tools for Haskell:
a) HPC (Haskell program coverage) tool kit

  1. Tools for Python:
a) Mc Cabe IQ
b) Fig leaf
c) Pester
d) Coverage.py

  1. Tools for PHP:
a) Mc Cabe IQ
b) PHP unit

  1. Tools for Ruby:
a) Rcov
b) Mc Cabe IQ
c) Simple cov
d) Cover Me

  1. Tools for Ada:
a) GNAT coverage
b) Mc Cabe IQ
c) Rapi Cover

Out of all the above mentioned tools for C and C++, the bulls eye coverage has proven to be the best code coverage analyzer in terms of reliability, usability and platform support etc. 
This coverage analyzer is different from the other analyzers in the following ways:
  1. Better coverage measurement
  2. Wide platform support
  3. Rigorously tested
  4. Efficient technical support
  5. Quite easy to use.
- Using this tool it can be determined that how much of the software system’s or application’s code was tested and this information later can be employed to focus your testing efforts and areas that require some improvement.
- With the bullseye coverage a more reliable code can be created and time can be saved. 
- The function coverage provided by the bulls eye coverage gives you a very high precision.

You can include or exclude the parts of the code of your choice. And what more? You can even merge the results you obtained from the distributed testing plus the run time code can also be included from custom environments. 


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