ENRE (ENtity Relationship Extractor ) is a tool for extraction of code entity dependencies(relationships) from source code. The resolved dependency types include:

ENRE supports analyzing source code written in Python, Go.

New Update!

ENRE has integrated type inference technique and type stub files (one of type hint practices) to enhance the extraction of Possible Dependencies in Python code.

Possible Dependencies are the syntactic dependencies indiscernible in source code due to the lack of explicit type references, in contrast with Explicit Dependencies.

You can learn more about this fresh feature and experience it in current version ENRE-v2.0.

To execute ENRE-type2.0.jar, you should set up JAVA envionment. Please referer to Set up JAVA environment.

ENRE contains Python scripts located in TypeExtractor for --from-type option. You should install Python in your local environment, at least Python 3.8 version.

TypeExtractor also requires several third-party tools listed in requirements.txt. You can install them by running the following command.

pip install -r requirements.txt

Why needs at least Python 3.8? The Python code in ENRE use Python ast library to find locations of objects, and some attributes (i.e., end_lineno,end_col_offset) of ast.node are only supported in Python3.8 and later. 

You can follow our enre-type-QA.md for possible solutions if configuring Python ENV fails.

The released jar of ENRE is named as ENRE-type2.0.jar.

Now, everthing is already prepared well. Let's use ENRE to analyze source code. The usage command is:

java -jar <executable> <lang> <dir> <include-dir> <project-name> [--from-type] [stub-dir]

• . The executable jar package of ENRE.
• . The language of source code that will be analyzed. It can be python or golang.
• . The path of the source code that will be analyzed.
• . The github url of source code. It only works when analyzing golang projects. Set it "null" when analyzing python projects.
• . A short alias name of the anayzed source code project.
• [--from-type]. Optional argument to add dependencies deduced from type infomation.
• [stub-dir]. Python stub file directory, used with --from-type option.

Use ENRE to analyze a demo project "fire" written in Python:

#in linux platform 
$java -jar ENRE-type2.0.jar  python  demo-projects/fire   null  fire   

#in windows platform
$java -jar ENRE-type2.0.jar  python  demo-projects\fire   null  fire 

After analysis, ENRE finally outputs the resovled entities and dependencies in JSON, XML, DOT files in new-generated fire-out/ directory.

Use ENRE to analyze a demo project "beego" written in Go:

#in linux platform 
$java -jar ENRE-type2.0.jar  golang  demo-projects/beego   github.com/astaxie/beego  beego  

#in windows platform
$java -jar ENRE-type2.0.jar  golang  demo-projects\beego   github.com/astaxie/beego  beego

After analysis, ENRE finally outputs the resovled entities and dependencies in JSON, XML, DOT files in new-generated beego-out/ directory.

[ENRE video introduction] (https://www.youtube.com/watch?v=BfXp5bb1yqc&t=43s)

Use ENRE to analyze a demo project django written in python with type stub infomation.

#in windows platform
$java -jar ENRE-type2.0.jar  python  demo-projects\django   null  django --from-type demo-projects\django-stubs

Besides outputting similar files to the Example I and Example II, this command will generate type infomation into django-type-info.csv and thus possible dependencies into deps-from-type.json.

You can follow enre-type-QA.md for possible solutions if coming across errors when running Example III.

You can reference the following papers if you use ENRE or feel interested in knowing more about it.

@inproceedings{2020ase-jin,
    title={Exploring the Architectural Impact of Possible Dependencies in Python Software},
	
    author={Jin, Wuxia and Cai, Yuanfang and Kazman, Rick and Zhang, Gang and Zheng, Qinghua and Liu, Ting},
    booktitle={2020 35th IEEE/ACM International Conference on Automated Software Engineering (ASE)},
    pages={1--13},
    year={2020},
    organization={IEEE}
    }

@inproceedings{2019icse-jin,
  title={ENRE: a tool framework for extensible eNtity relation extraction},
  
  author={Jin, Wuxia and Cai, Yuanfang and Kazman, Rick and Zheng, Qinghua and Cui, Di and Liu, Ting},
  booktitle={Proceedings of the 41st International Conference on Software Engineering: Companion Proceedings},
  pages={67--70},
  year={2019},
  organization={IEEE Press}
}

ENRE Introduction Video

MIT