EagleVision

Why use this tool

This tool will help in uncovering the details in a code repository. For example,

• Patterns in the code

• Type of asserts used in the test functions

• Test functions with no assert / pattern analysed

• Similarity in the source code/ test code functions

Note: Similarity analysis uses cosine algorithm, if the repo path given for root and repo size is relatively large, re consider to give sub-folders, Similarity analysis bound to take long time, since the computation is in memory if not provided with adequate size expect potential memory overflow

• Cyclomatic complexity of functions

• Repository statistics like, Type of file, LOC, Comments, Code etc.

Dependencies

• python 3.8 : 64 bit

• python packages (functiondefextractor, similarity-processor, lizard)

• cloc package npm i -g [email protected] https://www.npmjs.com/package/cloc Note: cloc has a dependency for pearl, if not installed please install pearl from https://www.perl.org/

• third party packages [Ctags, grep]

Installation

INSTALL.md

Usage

Commandline

>>>python -m eaglevision --p "path\to\input\json"

• sample json input,

[
  {
    "path": "repo/path",
    "run_pattern_match":true,
    "run_similarity":true,
    "extraction_annotation": null,
    "extraction_delta": null,
    "extraction_exclude": "*/test_resource/*",
    "pattern_match": ["assert"],
    "pattern_seperator": ["("],
    "similarity_range": "70,100",
    "run_cloc_metric":true,
    "cloc_args": "--exclude-dir=src --exclude-ext=*.cpp,*.java",
    "run_cyclomatic_complexity":true,
    "cyclo_args": "-l java  -l python",
    "cyclo_exclude": ["*.cpp","*.java"],
    "report_folder": null
  }
]

• Input Description,

    "path": Path of the repository to be analysed
    "run_pattern_match": On/OFF switch for running Pattern match
    "run_similarity": On/OFF switch for running Similarity check
    "extraction_annotation": Functions with this annotation will be
                             extracted else all functions
    "extraction_delta": If substring of annotation is given,
                        this input (integer value) will take number of
                        lines above and below the annotation to report,
    "extraction_exclude": Pattern to exclude for Similarity and Pattern check
    "pattern_match": Type of pattern to analyse in the source code
    "pattern_seperator": Seperator in the pattern, left side of which will
                         be used for pivot reporting
    "similarity_range": Range of similarity of interest example: "70,100",
    "run_cloc_metric": On/OFF switch for running Cloc / types of
                      files/number etc in the repo
    "cloc_args": Any additional args for Cloc tool
                 example:"--exclude-dir=src --exclude-ext=*.cpp,*.java",
    "run_cyclomatic_complexity":On/OFF switch for running cyclomatic complexity check,
    "cyclo_args": Any additional args for Lizard / cyclomatic complexity tool
                 example:"-l java  -l python"
    "cyclo_exclude": Pattern to exclude for cyclomatic complexity check
                     example: ["*.cpp","*.java"]
    "report_folder": Path where report to be placed, if null will be using the path of repo

Note:

All the inputs are taken from the json file

1. Do not forget to have the json as list [...]

2. Make sure pattern_match and pattern_seperator is of same length list if you are not interested in any pattern_seperator for s specific pattern_match , mark it null in pattern_seperator

3. Make sure mark it null if a string or list parameter is not used

4. Make sure mark it true/false for bool type

refer https://www.npmjs.com/package/cloc for cloc args
refer https://pypi.org/project/lizard/ for cyclo args
refer https://pypi.org/project/functiondefextractor/ for extraction_exclude
refer https://pypi.org/project/similarity-processor/ for similarity

Output

• Output will be available in same folder as path given in json under EagleVisionReport

Contact

MAINTAINERS.md

License

License.md