Difference: FRCVLabMLSA_execution (1 vs. 5)

Revision 52017-07-12 - AnneMarieBogar

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META TOPICPARENT name="FRCVLabMLSA"
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Execution

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MLSA_logo.png Execution

  To run the software:
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-- (c) Fordham University Robotics and Computer Vision

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META FILEATTACHMENT attachment="MLSA_logo.png" attr="" comment="" date="1499887620" name="MLSA_logo.png" path="MLSA_logo.png" size="39428" user="AnneMarieBogar" version="1"

Revision 42017-07-12 - AnneMarieBogar

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META TOPICPARENT name="FRCVLabMLSA"
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  To run the software:
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1. Download software from https://git.io/MLSA

2. Run mlsapath.bash in the mlsa folder (adds mlcg.py to PATH) with command: $source mlsapath.bash

3. On the terminal, run the mlcg command with the desired folder or programs as arguments: $mlcg.py [list of args]

.

A good way to test if your MLSA installation is operating correctly is to test the code on the test programs in the test folder

1. Run the command: $python testcode.py 0

2. A document titled 'stats' will show if there are any differences between the code you generated and the ideal code

3. Delete the generated code by running the command: $python testcode.py -1

2. Repeat with numbers 1-5

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On the terminal, run the mlcg command with the desired folder or programs as arguments:
  • $mlcg.py [list of args]
A good place to start is by testing out the code in MLSA's test folder by running the command:
  • $mlcg.py test/test5
The multilingual pipeline is called for all the programs in test5 and a single call graph is generated. Procedure calling between files in the same and different languages will be identified (for the limited set of interoperability calls that have been implemented) and the call graph will reflect this, but programs with no procedure calls in common are fine too. The resulting call graph is a forest of trees. Recursion is flagged after one full cycle and several other kind of interlanguage calls are also flagged, such as circularity in a system and the inability to determine a program called through one of the three APIs used for interoperability.
 

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Revision 32017-07-11 - AnneMarieBogar

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META TOPICPARENT name="FRCVLabMLSA"
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  To run the software:

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1. Copy all the source files to be analyzed into the mlsa/bin/ folder (including additional .h and .c files)
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1. Download software from https://git.io/MLSA
 
Changed:
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2. On the terminal, run the command:
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2. Run mlsapath.bash in the mlsa folder (adds mlcg.py to PATH) with command: $source mlsapath.bash
 
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./mlsa_run [list of args]
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3. On the terminal, run the mlcg command with the desired folder or programs as arguments: $mlcg.py [list of args]
 
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list of args is the set of source programs to be combined in the final call graph.
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Added:
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A good way to test if your MLSA installation is operating correctly is to test the code on the test programs in the test folder

1. Run the command: $python testcode.py 0

2. A document titled 'stats' will show if there are any differences between the code you generated and the ideal code

3. Delete the generated code by running the command: $python testcode.py -1

2. Repeat with numbers 1-5

 

Permissions

  • Persons/group who can view/change the page:

Revision 22016-07-27 - DamianLyons

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META TOPICPARENT name="FRCVLabMLSA"
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  ./mlsa_run [list of args]
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    • list of args is the set of source programs to be combined
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list of args is the set of source programs to be combined
  in the final call graph.

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Revision 12016-07-26 - DamianLyons

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META TOPICPARENT name="FRCVLabMLSA"
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Execution

To run the software:

1. Copy all the source files to be analyzed into the mlsa/bin/ folder (including additional .h and .c files)

2. On the terminal, run the command:

./mlsa_run [list of args]

    • list of args is the set of source programs to be combined in the final call graph.

Permissions

  • Persons/group who can view/change the page:
  • Set ALLOWTOPICCHANGE = FRCVRoboticsGroup

-- (c) Fordham University Robotics and Computer Vision

 
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