BACKEND : merge conflicts resolved

backend/app.py

@@ -11,7 +11,7 @@ from routes.module_routes import module
 from routes.assignment_routes import assignment
 from routes.diagram_routes import diagram
 from routes.submission_routes import submission
-from routes.plagiarism_routes import use_case_diagram_plagiarism
+
 APP_ROOT = os.path.dirname(os.path.abspath(__file__))
 
 OUTPUTS_GENERATED_DOT_FILES_PATH = os.path.join('outputs', 'generated_dot_files')
@@ -47,7 +47,6 @@ app.register_blueprint(module)
 app.register_blueprint(assignment)
 app.register_blueprint(diagram)
 app.register_blueprint(submission)
-app.register_blueprint(use_case_diagram_plagiarism)
 
 
 @app.before_first_request

backend/models/attribute_model.py

@@ -3,9 +3,9 @@ from config.database import db
 
 class Attribute(db.Model):
     id = db.Column(db.Integer, primary_key=True)
-    data_type = db.Column(db.String(50), nullable=False)
+    data_type = db.Column(db.String(50))
     name = db.Column(db.String(50), nullable=False)
-    access_spec = db.Column(db.String(50), nullable=False)
+    access_spec = db.Column(db.String(50))
     class_id = db.Column(db.Integer)
 
     def __repr__(self) -> str:

backend/models/method_model.py

+from config.database import db
+
+
+class Method(db.Model):
+    id = db.Column(db.Integer, primary_key=True)
+    return_type = db.Column(db.String(50))
+    name = db.Column(db.String(50), nullable=False)
+    access_spec = db.Column(db.String(50))
+    class_id = db.Column(db.Integer)
+
+    def __repr__(self) -> str:
+        return 'Method>>> {self.content}'

backend/routes/plagiarism_routes.py

-import requests
-from sqlalchemy import func
-from flask import Blueprint, jsonify, request
-from constants.http_status_codes_constant import HTTP_200_OK, HTTP_400_BAD_REQUEST, HTTP_201_CREATED, \
-    HTTP_500_INTERNAL_SERVER_ERROR
-from config.database import db
-# from datetime import datetime
-
-from models.actor_and_use_case import ActorANDUseCase
-
-from models.extend_relationship import ExtendRelationship
-
-from models.include_relationship import IncludeRelationship
-
-from models.use_case_generalization_relationship import UseCaseGeneralizationRelationship
-
-from models.use_case_association_relationship import UseCaseAssociationRelationship
-
-from models.use_case_answer import UseCaseAnswer
-
-from models.actor_generalization_relationship import ActorGeneralizationRelationship
-
-from services.similarity import similarity_components
-
-use_case_diagram_plagiarism = Blueprint('use_case_diagram_plagiarism', __name__,
-                                        url_prefix='/api/v1/use_case_diagram_plagiarism')
-
-
-@use_case_diagram_plagiarism.get('/similarities')
-def get_use_case():
-
-    extent_component = None
-    include_component = None
-    user_case_association_component = None
-    user_cases_generalization_component = None
-    actor_generalization_component = None
-    actor_association_component = None
-
-    includes = IncludeRelationship.query.all()
-    extents = ExtendRelationship.query.all()
-    user_cases = ActorANDUseCase.query.all()
-    user_case_associations = UseCaseAssociationRelationship.query.all()
-    user_cases_generalizations = UseCaseGeneralizationRelationship.query.all()
-    actor_generalizations = ActorGeneralizationRelationship.query.all()
-
-    for user_case in user_cases:
-        if user_case.type == "use case":
-            for extent in extents:
-                if user_case.id == extent.connected_component_01:
-                    extent_component = user_case
-                    similarity_components(extent_component.use_case_answer, extent_component.text)
-                    print("Extend component 1 : ", extent_component.text)
-                elif user_case.id == extent.connected_component_02:
-                    extent_component = user_case
-                    similarity_components(extent_component.use_case_answer, extent_component.text)
-                    print("Extend component 2 : ", extent_component.text)
-
-            for include in includes:
-                if user_case.id == include.connected_component_01:
-                    include_component = user_case
-                    similarity_components(include_component.use_case_answer, include_component.text)
-                    print("Include component 1 : ", include_component.text)
-                elif user_case.id == include.connected_component_02:
-                    include_component = user_case
-                    similarity_components(include_component.use_case_answer, include_component.text)
-                    print("Include component 2 : ", include_component.text)
-
-            for user_case_association in user_case_associations:
-                if user_case.id == user_case_association.connected_component_01:
-                    user_case_association_component = user_case
-                    similarity_components(user_case_association_component.use_case_answer,
-                                          user_case_association_component.text)
-                    print("User cases association component 1 : ", user_case_association_component.text)
-                elif user_case.id == user_case_association.connected_component_02:
-                    user_case_association_component = user_case
-                    similarity_components(user_case_association_component.use_case_answer,
-                                          user_case_association_component.text)
-                    print("User cases association component 2 : ", user_case_association_component.text)
-
-            for user_cases_generalization in user_cases_generalizations:
-                if user_case.id == user_cases_generalization.connected_component_01:
-                    user_cases_generalization_component = user_case
-                    similarity_components(user_cases_generalization_component.use_case_answer,
-                                          user_cases_generalization_component.text)
-                    print("User cases generalization Component 1 :  ", user_cases_generalization_component.text)
-                elif user_case.id == user_cases_generalization.connected_component_02:
-                    user_cases_generalization_component = user_case
-                    similarity_components(user_cases_generalization_component.use_case_answer,
-                                          user_cases_generalization_component.text)
-                    print("User cases generalization Component 2 : ", user_cases_generalization_component.text)
-
-        elif user_case.type == "actor":
-            for actor_generalization in actor_generalizations:
-                if user_case.id == actor_generalization.connected_component_01:
-                    actor_generalization_component = user_case
-                    similarity_components(actor_generalization_component.use_case_answer,
-                                          actor_generalization_component.text)
-                    print("Actor generalization component 1 : ", actor_generalization_component.text)
-                elif user_case.id == actor_generalization.connected_component_02:
-                    actor_generalization_component = user_case
-                    similarity_components(actor_generalization_component.use_case_answer,
-                                          actor_generalization_component.text)
-                    print("Actor generalization component 2 : ", actor_generalization_component.text)
-
-
-            for actor_association in user_case_associations:
-                if user_case.id == actor_association.connected_component_01:
-                    actor_association_component = user_case
-                    similarity_components(actor_association_component.use_case_answer,
-                                          actor_association_component.text)
-                    print("Actor association component 1 : ", actor_association_component.text)
-                elif user_case.id == actor_association.connected_component_02:
-                    actor_association_component = user_case
-                    similarity_components(actor_association_component.use_case_answer,
-                                          actor_association_component.text)
-                    print("Actor association component 2 : ", actor_association_component.text)
-
-    return jsonify({"Message": "Success"}), HTTP_200_OK
-
-
-@use_case_diagram_plagiarism.get('/use_case_plagiarism_percentage')
-def get_actor():
-    user_cases = ActorANDUseCase.query.all()
-    use_case_answers = UseCaseAnswer.query.all()
-
-    all_count = db.session.query(ActorANDUseCase.use_case_answer,
-                                 func.count(ActorANDUseCase.use_case_answer)).group_by(
-        ActorANDUseCase.use_case_answer).all()
-
-    actor_similarity = db.session.query(ActorANDUseCase.use_case_answer,
-                                        func.count(ActorANDUseCase.plagiarism_count)).filter_by(
-        plagiarism_count=1).group_by(
-        ActorANDUseCase.use_case_answer).all()
-
-    for use_case_answer in use_case_answers:
-        print(use_case_answer.id)
-        counter = 0
-        counter1 = 0
-
-        for user_case in user_cases:
-            if user_case.use_case_answer == use_case_answer.id:
-                counter += 1
-                if user_case.plagiarism_count == "1":
-                    counter1 += 1
-        print("All use cases and actors count :", counter)
-        print("similarity count :", counter1)
-        if counter != 0:
-            plagirism_count = counter1/counter * 100
-            print("Plagiarism Percentage :", plagirism_count)
-
-
-
-
-
-
-    return jsonify({"Message": "Success"}), HTTP_200_OK

backend/routes/submission_routes.py

@@ -5,7 +5,7 @@ from flask_jwt_extended import jwt_required, get_jwt_identity
 
 from constants.http_status_codes_constant import HTTP_400_BAD_REQUEST, HTTP_200_OK
 
-from services.class_model_detection_service import component_separation
+from services.class_diagram_class_detection_service import component_separation
 from models.actor_and_use_case import ActorANDUseCase
 from services.submission_service import save_submission
 from services.use_case_model_detection_service import model_object_detection

backend/services/question_preprocess_service.py

@@ -11,15 +11,15 @@ def remove_unwanted_values(data):
     return data
 
 
-# removing duplicates
-def remove_duplicates(data):
-    return list(set(data))
+# # removing duplicates
+# def remove_duplicates(data):
+#     return list(set(data))
 
 
-# punctuation removal
+# punctuation removing
 def remove_punctuation(sentence):
-    text_no_punct = [token for token in sentence if not token.is_punct]
-    cleaned_sentence = ' '.join(token.text for token in text_no_punct)
+    text_without_punctuation = [token for token in sentence if not token.is_punct]
+    cleaned_sentence = ' '.join(token.text for token in text_without_punctuation)
     return cleaned_sentence
 
 
@@ -37,31 +37,32 @@ def main(scenario, assignment_type):
     del sentences[-1]
 
     # creating required lists
-    nc = []
+    nouns_pronouns = []
     cleaned_extracted_actions = []
     cleaned_sentences = []
-    splitted_actions_array = []
+    splitted_actions_and_actor_array = []
 
     # looping through each sentence
     for sentence in sentences:
+        # getting actors using nouns pronouns
         res = get_nouns_pronouns(sentence)
-        nc.append(str(res))
+        nouns_pronouns.append(str(res))
         cleaned_sentence = remove_punctuation(sentence)
         cleaned_sentences.append(cleaned_sentence)
 
-        splitted_actions = split_actions(str(cleaned_sentence))
-        splitted_actions_array.append(splitted_actions)
+        splitted_actions_and_actor = split_actions(str(cleaned_sentence))
+        splitted_actions_and_actor_array.append(splitted_actions_and_actor)
 
-        extracted_actions = get_actions(splitted_actions)
+        extracted_actions = get_actions(splitted_actions_and_actor)
 
         if extracted_actions is not None:
             cleaned_extracted_actions.append(extracted_actions)
 
     # remove duplicates of the actors
-    nc = list(dict.fromkeys(nc))
-    data = remove_unwanted_values(nc)
+    nouns_pronouns = list(dict.fromkeys(nouns_pronouns))
+    data = remove_unwanted_values(nouns_pronouns)
 
-    extracted_relationships = get_include_extend_relationships(splitted_actions_array)
+    extracted_relationships = get_include_extend_relationships(splitted_actions_and_actor_array)
     actors_and_use_cases_array = identify_use_cases(cleaned_extracted_actions)
 
     if assignment_type == 1:

backend/services/similarity.py

-from models.actor_and_use_case import ActorANDUseCase
-
-from config.database import db
-
-
-def similarity_components(use_case_answer, use_case_text):
-    user_cases = ActorANDUseCase.query.all()
-    for use_case1 in user_cases:
-        if use_case1.use_case_answer != use_case_answer and use_case1.text == use_case_text:
-            use_case1.plagiarism_count = 1
-
-            db.session.add(use_case1)
-            db.session.commit()

backend/services/tokenization_service.py

@@ -24,12 +24,14 @@ def get_nouns_pronouns(sentence):
             return token
 
 
+# removing punctuations
 def remove_punctuation(sentence):
     text_no_punct = [token for token in sentence if not token.is_punct]
     cleaned_sentence = ' '.join(token.text for token in text_no_punct)
     return cleaned_sentence
 
 
+# get actions and actors
 def split_actions(sentence):
     split_string = "should be able to "
     if split_string in sentence:
@@ -37,16 +39,18 @@ def split_actions(sentence):
         return extracted_string
 
 
-def get_actions(splitted_action):
+# get
+def get_actions(splitted_action_and_actor):
     temp_array = []
-    if splitted_action is not None and '|' in splitted_action[1]:
-        res = splitted_action[1].split(' | ')
-        # print('res',res)
-        temp_array.append(splitted_action[0])
+    if splitted_action_and_actor is not None and '|' in splitted_action_and_actor[1]:
+        res = splitted_action_and_actor[1].split(' | ')
+
+        temp_array.append(splitted_action_and_actor[0])
         temp_array.append(res[0])
+        print(temp_array)
         return temp_array
     else:
-        return splitted_action
+        return splitted_action_and_actor
 
 
 def get_sentences(text):

backend/tensorflow_models/class/label/label_map.pbtxt

 item {
     id: 1
-    name: 'class'
+    name: 'association'
 }
 
 item {
     id: 2
-    name: 'relationship'
+    name: 'class'
+}
+
+item {
+    id: 3
+    name: 'composition'
+}
+
+item {
+    id: 4
+    name: 'indirect association'
+}
+
+item {
+    id: 5
+    name: 'inheritance'
+}
+
+item {
+    id: 6
+    name: 'interface'
+}
+
+item {
+    id: 7
+    name: 'realization'
 }
\ No newline at end of file