Usage#

plagcheck provides the following classes & methods:

check(files, lang, user_id)#

• Parameters :
• files : Program Files.
• lang : The Programming Language.
• output : Moss UserID.

Demo:

"""Usage example"""
import os
import pprint
from plagcheck.plagcheck import check, insights, share_scores

from dotenv import load_dotenv
load_dotenv()

language = "java"
userid = os.environ["USER_ID"]


moss = check(language, userid)

moss.addFilesByWildCard("testfiles/test_java*.java")

# or moss.addFile("testfiles/test_python.py")

moss.submit()

print(moss.getHomePage())

result = moss.getResults()

pprint.pprint(result)

# print potential distributor-culprit relationships
pprint.pprint(insights(result))
# print frequency of each shared solution
pprint.pprint(share_scores(result))

1. submit()#

Parameters : None
Return Type : None
Description: Submits the program on Moss.
Demo:

c.submit()

2. getHomePage()#

Parameters : None
Return Type : String
Description: Returns the Moss Result HomePage URL
Demo:

c.getHomePage()

3. getResults()#

Parameters : None
Return Type : List
Description: Returns the scraped data from Moss Results .
Demo:

c.getResults()

getResults() returns the following list of dictionaries:

[
  {
    "file1":"filename1.py",
    "file2":"filename2.py",
    "percentage": 34,
    "no_of_lines_matched": 3,
    "lines_matched":[["2-3", "10-11"]]
  },
....
]

Each dict item contains the following items:

• file1 & file2 : The pair of file names that have similar code.

• percentage : It is the the percentage of the code in one file considered to match code in the other file.

• lines_matched : Lines Matched is approximately the number of lines of code that matched between 2 given files.

For example : If lines_matched is [['88-99','119-131']]

Then the line numbers 88-99 of file1 matched with lines 119-131 of file2.

lines_matched is a list of lists indicating all line number matches between 2 code files.

For both measures(lines_matched & percentage), higher numbers mean more code matches.

4. addFilesByWildCard()#

Parameters : String
Return Type : None
Description: Add multiple files.
Demo:

c.addFilesByWildCard("testfiles/test_python*.py")
# This will add all the files having names like, test_python2, test_python5 etc.

5. addFile()#

Parameters : String
Return Type : None
Description: Add a single file for submission.
Demo:

c.addFile("testfiles/test_python.py")

6. addBaseCode()#

Parameters : String
Return Type : None
Description: Add an allowed code file which is use by Moss to ignore results matching with this file
Demo:

c.addBaseCode("/base.py")

• Moss normally reports all code that matches in pairs of files. When a base file is supplied, program code that also appears in the base file is not counted in matches.
• A typical base file will include, for example, the instructor-supplied code for an assignment. Multiple Base files are allowed.
• You should use a base file if it is convenient; base files improve results, but are not usually necessary for obtaining useful information.

---

share_scores()#

Parameters : Moss Results(returned by getResults())
Return Type : Dict
Description: Share Score is a utility which returns frequency of every individual file.
Demo:

print(share_scores(moss_data))

# Will return
"""
{'testfiles/test_python.py': 2,
 'testfiles/test_python2.py': 2,
 'testfiles/test_python3.py': 2}
"""

Share Score is basically the frequency of each file appearing in Moss Results. i.e Higher the frequency, the more is that solution "shared" by different files.

insights()#

Parameters : Moss Results(returned by getResults())
Return Type : Dict
Description: See Insights.
Demo:

print(insights(moss_data))