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How to optimize your local machine for the Kiuwan Local Analyzer (KLA)

Here are some things you should consider

Local machine’s characteristics and KLA configuration

As said before, if your source code contains Java, Javascript and JSP files, there will be 9 steps (rules, metrics and duplication analysis for every technology).

 

Info

Every analysis step is accomplished by executing a new JVM.

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to properly configure your analyses. 

Optimize the Java Virtual Machine

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Every step is performed through the execution of a JVM process.

Java 8 (64 bits) or above —either JDK or JRE— is required.

 
 

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titleFor Linux/Unix users

IMPORTANT for LINUX/UNIX users:

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Below link will help you to fix it:

By default,

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 KLA comes with pre-configured default values:

  • max

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  • memory to use during every single step

  • max

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  • duration time (timeout) of every single step

These parameters are configured

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through KLA configuration mechanism, please do not modify KLA scripts to include JVM flags such as -Xmx, use the mechanisms Kiuwan provides.

Info
titleFor Linux/Unix users

Please check /dev/random configuration of JVM. This may produce severe performance problems (java urandom Entropy).

Here is how to fix it: Analyses are very Slow in Unix Linux, or Halt when Uploading Results to Kiuwan

Single and parallel execution of analyses

 

Every

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step in an analysis with the KLA is executed sequentially

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, following the order

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below: 

 

  1. For

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  1. each technology

    1. rule analysis

    2. metrics analysis

    3. clone detection

  2. Report generation, encryption and uploading to Kiuwan cloud

 

Every step is executed by a “new” JVM

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(Java 8 or above required) and the Kiuwan configuration applies to all of those JVM instances.

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Therefore, those memory-cpu consuming steps may result in full use (near to 100%) of a CPU core.

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If your source code contains more than one technology, it will execute each step for each technology. 

If the machine running KLA analyses contains more available CPUs, you can run

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parallel

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analyses by executing additional instances of KLA.

In a parallel KLA execution scenario, every running analysis is completely independent from each other, so you can execute multiple analysis provided your machine has enough CPUs.

Memory configuration

By default, the KLA comes pre-configured with the

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following memory default

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values (analyzer.properties):

 

Code Block
languagexml
# Starting size for heap memory (128m = 128 Megabytes)
memory.start=128m
# Maximum size for heap memory (1024m = 1 Gigabyte)
memory.max=1024m
# Stack memory, per thread (1024k = 1 Megabyte)
stack.size=2048k

 

If

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your local analysis ends with

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an Out of Memory (OOM) error, you need

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to increase the max

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memory allocated to the JVM (by default, 

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1GB).

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The troubleshooting links below can help you

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identify OOM errors:

You can configure Kiuwan to increase memory limits either for the whole installation or per application.

  • If you are using

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ATTENTION:

Depending on your available physical memory

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, OS and JVM version,

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 if you increase the max memory the JVM might not

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In these cases, stopping unneeded processes (or restarting the machine) can free unneeded allocated memory. Nevertheless, sometimes this does not free memory so you need to test with lower memory values.

 

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If you notice the process is performing

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a high activity of JVM garbage collection, even without an OOM, this situation may indicate your analysis needs more memory and the performance is suffering due to

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GC activity. In

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this case, try to increase the max memory, most probably the analysis performance will be faster.

 

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Warning

Do not increase

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the memory indefinitely.

If

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your analysis needs more than 2GB to finish, it might be a clue of an existing memory leak or some other

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issue.

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If this

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happens,

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contact Kiuwan Technical Support and report this situation.

 

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Timeout configuration

By default, every step of a local analysis is

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configured to

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a default max execution time (60 minutes) (analyzer.properties):

 

Code Block
languagexml
# Timeout to use for max execution time of each analysis step (in msecs)
 timeout=3600000

 

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The default value is often enough for most

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analyses, but depending on several circumstances (code size, memory, ruleset, etc) could not be enough and

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a timeout error will occur (Timeout Killed the Subprocess).

If this happens

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, increase the default value.

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