SlideShare a Scribd company logo
1 of 7
Download to read offline
IOSR Journal of Computer Engineering (IOSR-JCE)
e-ISSN: 2278-0661,p-ISSN: 2278-8727, Volume 18, Issue 1, Ver. I (Jan – Feb. 2016), PP 37-43
www.iosrjournals.org
DOI: 10.9790/0661-18113743 www.iosrjournals.org 37 | Page
Towards Automated Generation of ER-Diagram using a Web
Based Approach
Amol V. Khaire1
, Pramod B. Mali2
1
PG Student, Department of Computer Engineering, Smt. Kashibai Navale College of Engineering, Vadgaon
Bk, Pune, India
2
Assistant Professor, Department of Computer Engineering, Smt. Kashibai Navale College of Engineering,
Vadgaon Bk, Pune, India
Abstract : Diagrams plays an important role in the software development process. Drawing the diagrams
manually is the time consuming task, so there are many tools to draw and modify the diagram. From all the
diagrams ER (Entity Relationship) Diagram plays an important role in the software development process in
Computer Engineering. This paper will describe the existing tools and presents a Web Application to generate
the Entity Relationship Diagram automatically. This Web Application will allow us to generate Entity
Relationship Diagram automatically by a form filling method which will take the Entity, Attribute and
Relationship as an input and gives the Entity Relationship Diagram as output automatically.
Keywords - Automated ER-Diagram, Entity Relationship Diagram, Software Development Process, Web
Application
I. INTRODUCTION
There are numerous Diagrams like block diagrams, organizational chart for showing the hierarchical
structure, network diagram of an association, Pie Chart, Flow Chart, ER-Diagram and so forth. In any case, out
of every one of these Diagrams ER-Diagram is critical in the programming development process. In today's
business world, databases are almost significant, as they describe information about an organization and entity
relationship modeling is by a wide margin the most well-known approach to express the expository
consequence of an early stage in the creation of the new database [1]. In this paper, we are going to see the
distinction between the ER-Diagram creating tools which is a manual procedure, additionally require the lots of
knowledge about tools and a web Application that we are going to create. Presently there are different tools to
draw the diagram. These tools are not at risk for automatic generation of ER-Diagram (Entity Relationship
graph). These tools provide the platform for the user to represent the ER-diagram using various symbols.
Currently used tools for creation of ER-diagram are Edraw [7], DIA [8] and so forth. These tools are producing
the Entity Relationship Diagram manually.
This infer to requirement of dragging and dropping the items which are required to draw the Entity
Relationship Diagram. It should to be noticed that there are numerous representations of ER-Diagram for the
same problem. We additionally plan to implement the web Application in the three stages
Step1:- Taking the input from the user, i.e. Entity, Attribute and Relationships
Step2:- Providing input to a web form.
Step3:- Generate and Store the ER-Diagram.
DIA [7] and Edraw [8] is a manual tool to produce ER-Diagram. Paper [1] has not more concentrate
on ER-Diagram, paper [2] has not Clear thought regarding the how to produce an ER-diagram naturally, paper
[3] have the troublesome procedure for creating ER-Diagram automatically, so we are developing the Web
application which is generating the Entity Relationship Diagram automatically. As this process is automatic this
can be very useful for the user.
II. LITERATURE SURVEY
ADG (Auto-Diagram generator) tool is used to create the Flow Chart, Block Diagram and Entity
Relationship Diagram by form filling and text selection method [1]. Form filling strategy used is one of the best
methodologies for a novice user to determine the diagram prerequisites. The diagram generator and editor is the
principle part of this tool. DeZign tool is utilized for generation of a diagram [2]. DeZign tool creates the
Extended Entity Relationship Diagram and this is utilizing the form filling system as like the ADG (auto graph
generator) tool. DeZign utilize the three modules to create the Diagram. DeZign device utilizes a Simple
English explanation as information and gives the Entity Relationship Diagram as a yield. Paper [3] Explains
about an ABCM (Association based theoretical model) and how the ABCM utilizes a connection Adaptive way
to deal with creating the Entity Relationship chart. Before creating the ER diagram a graphical tool called
Association based theoretical model is utilized to discover a relationship between a two or more objects
Towards Automated Generation of ER-Diagram using a Web Based Approach
DOI: 10.9790/0661-18113743 www.iosrjournals.org 38 | Page
described in the business depictions. The ABCM can deal with a three or more objects and also two ones in a
breath.
AER (Articulated Entity Relationship) is created from the Entity-Relationship diagram [5]. The AER is an
expansion to the ER-graph. In the AER, diagram is produced automatically, but the ER-diagram is taken
manually. NLP (natural language processing) is used for producing the Entity-Relationship diagram [6].
Heuristic methodology is utilized for producing the Entity Relationship diagram. The semantic Heuristics will
be utilized to decide the Entity, Attribute and Relationships from a database specification. Heuristics are a
superior methodology however the Diagram generation process is complicated because of this. Syntactic
Heuristics are executed in the ER-converter. Diagram generation algorithms are given in [4]. Building block
diagrams, graphical objects, diagram resizing and graph altering algorithms are depicted. However, the
procedure utilized is manual.
Table 1 demonstrates the correlation between the distinctive tools like ADG, ABCS and DeZign. Table 1
additionally indicates how these devices are ideal to produce the Entity relationship graph.
Right now there are numerous tools existing for the generation of an ER-diagram (entity relationship
diagram). These tools are DIA [7], Edraw [8] and so on. DIA device is utilized to create the diagrams like
stream flow chart, block diagram, ER-Diagram and so on. In any case, before drawing the diagram we need to
first install that tool on our machine and should have knowledge about the DIA tool. In the DIA process,
drawing diagram is manual. Thus, diagram generation process in DIA is tedious. Edraw is another tool as like
DIA which additionally utilizes the manual procedure to draw the diagram.
Tool Name Survey Details Findings
ADG Tool[1] This explains about Automating diagram
process and for atomization they use ADG
tool which uses the form filling method.
Tool explains about atomization
of other diagrams and does not
focus on ER-diagram.
DeZign Tool[2] This explains about automating diagram
process and use DeZign tool to generate
the Entity Relationship Diagram.
Clear thought regarding how to
produce ER-diagram
automatically is not clarified.
ABCS(Association-Based
Conceptual Based
Systems) Tool[3]
For ER-diagram generation process uses
ABCS(Association-Based Conceptual
Based Systems).This uses the Context
Adaptive approach to generate the ER-
Diagram
Difficult process for generating
ER-diagram automatically.
Table 1:- Comparison between Automated Tools
III. PROPOSED SYSTEM
Proposed system discusses about system architecture and mathematical model of automated ER-Diagram
generation.
3.1 System Architecture
System architecture indicates how we are developing the web Application to produce the Automated Entity
Relationship Diagram. Figure 1 demonstrates a System Architecture for producing the Entity Relationship
Diagram automatically. As the architecture is a web based so, we need to build up a web application. In
Automated ER-Diagram Generation we have the web page which will take the Entity, Attribute, Relationships
as data and giving the ER-Diagram as output. A Proposed plan for an automated ER-Diagram is partitioned into
the 3 modules.
Module1: Accepting Entity, Attribute and Relationships.
Module2: Generating ER-Diagram automatically.
Module3: Storing ER-Diagram onto the device.
In the module 1, we are accepting the Entity details, Attribute details and Relationship details from the user
through the user interface. Entity details contain the quantity of Entities, name of every Entity and type of each
entity. Attribute details contains the quantity of Attributes for respective entity, the name of each Attribute, the
type of each attribute. Relationship details contain the name of the relationship between any two entities. As
this procedure is on the web so in the wake of giving the data this data is sent to the server. At the point when
Towards Automated Generation of ER-Diagram using a Web Based Approach
DOI: 10.9790/0661-18113743 www.iosrjournals.org 39 | Page
data goes to a server then this data is saved into a database. This data will be given in the following module to
create the output.
In module 2, we are giving Entity detail, attribute details & Relationship details as input to this module and
generating the ER-Diagram automatically.
In module 3 we are taking the ER-Diagram which is created by the Module 2 and this Diagram is saved into
the format which a user is comfortable. After saving a file in this format the file is stored onto a storage device
and then provided to the user. The User needs to give all the data to create the ER-Diagram automatically.
Figure 1 shows the proposed design diagram which takes the input as an Entity, Attribute & Relationships.
Then this input information is provided on the web page which generates ER-Diagram automatically. Figure 1
shows this basic system architecture to generate the ER-Diagram. Arrows in the diagram show the input and
output to and from the web application. Initially a user gives an input which is provided to the webpage and
these web pages will give the output as the ER-Diagram as shown in the Diagram. Figure 1 also shows an IIS
(internet information server) Server. The ISS sever is the server on which our automated ER-Diagram
generation web application is running. When contrasted with the past devices this Web Application is the better
way to deal with produce ER-diagram furthermore as these are accessible on the web so it is easy to use for the
User.
Fig. 3.1: System Architecture for Automated ER-Diagram Generation.
3.2. Mathematical Model
Set Theory:
Let S be the set then, S= {EN, AT, RS}
Where,
EN=set of entities
AT=set of attributes
RS=set of relationships and
EN, AT and RS are represented as
EN= {E1, E2, E3,……….En}
AT= {A11, A12, A13,………. A1n,
A21, A22, A23,………. A2n,
An1, An2, An3,…...….. Ann}
RS= {R1, R2, R3…. Rn}
Towards Automated Generation of ER-Diagram using a Web Based Approach
DOI: 10.9790/0661-18113743 www.iosrjournals.org 40 | Page
IV. EXPERIMENTAL RESULTS
This section discusses about how ER-diagram is generated automatically. Screenshot 4.1, shows the Entity
filter details for three levels, i.e. low, middle and expert.
Screenshot 4.1: Entity filters Details.
Screenshot 4.2, shows the Attribute filter details for three levels, i.e. Low, Middle and Expert. Screenshot
4.3, shows the Relationship filter details for three levels, i.e. Low, Middle and Expert. Screenshot 4.4, shows
the low level ER-diagram which is generated by filtering Entity, Attribute and Relationship. Screenshot 4.5,
shows the Middle level ER-diagram which is generated by filtering Entity, Attribute and Relationship.
Screenshot 6 shows the Expert level ER-diagram which is generated by filtering Entity, Attribute and
Relationship.
Towards Automated Generation of ER-Diagram using a Web Based Approach
DOI: 10.9790/0661-18113743 www.iosrjournals.org 41 | Page
Screenshot 4.2: Attribute filters Details.
Screenshot 4.3: Relationship filters Details.
Towards Automated Generation of ER-Diagram using a Web Based Approach
DOI: 10.9790/0661-18113743 www.iosrjournals.org 42 | Page
Screenshot 4.4: Low level ER-Diagram.
Screenshot 4.5: Medium level E-R Diagram.
Towards Automated Generation of ER-Diagram using a Web Based Approach
DOI: 10.9790/0661-18113743 www.iosrjournals.org 43 | Page
Screenshot 4.6: Expert level E-R Diagram.
V. CONCLUSION
A Web Application for Automated generation of ER-Diagram provides a way to generate Automated ER-
diagrams, which makes it usable for a wide range of users. This Web Application is user friendly and rather
than drag and drop approach it uses an automated approach to generate the diagram. A user does not require
more knowledge to generate the diagrams as compared to other available tools.
A Web Based approach towards Automated ER-Diagram generation can be extended to generate the
Extended Entity Relationship Diagram (EED) automatically by providing input as an attribute, entity and so
forth. In future we can also extend this for generating all the UML diagrams like Use case diagram, Data Flow
diagram, Class Diagram and so forth.
REFERENCES
[1] Tabinda Sarwar, Uzma Arif, Wajiha Habib, Samna Zehra, “Automating The Diagram Generation Process”, International Journal of
Scientific and Engineering Research Volume 2, Issue 7, July-2011
[2] Dr. Muhammad Shahbaz, Dr. Syed Ahsan, ammad Shaheen, Rao Muhammad Adeel Nawab, Syed Athar Masood, University of
Engineering & Technology Lahore, Punjab Pakistan, "Automatic Generation of Extended ER Diagram Using Natural Language
Processing”, Journal of American Science, 2011
[3] Sangwon Lee, Namgyu Kim and Songchun Moon, Department of Management Engineering, Korea Advanced Institute of Science
and Technology, Seoul130-722, Korea, “Context Adaptive Approach for Automated Entity Relationship Modeling”, journal of
information science and engineering 26, 2229-2247 (2010).
[4] Tabinda Sarwar, Uzma Arif, Wajiha Habib Samana Zehra, “An Efficient and Simplest Algorithm for Generating Diagrams”,
International Journal of Scientific & Engineering Research Volume 2, Issue 7, July-2011,ISSN 2229-5518
[5] P. S. Dhabe, Dr. M. S. Patwardhan, Asavari A. Deshpande, M. L. Dhore, B.V. Barbadekar and H. K. Abhyankar, Department of
Computer Engineering, Vishwakarma Institute of Technology, Pune-411037, Maharashtra State, India, “Articulated Entity
Relationship Diagram for Complete Automation of Relational Database Normalization”, International Journal of Database
Management System, Volume 2, Num 2
[6] N. Omar, P. Hanna and P. Mc Kevitt, “Semantic Analysis in the Automation of ER Modelling through Natural Language
Processing”
[7] Edraw Max. Available:http://www.edrawsoft.com
[8] Dia. Available: http://www.diahome.org

More Related Content

What's hot

IRJET- A Study on Face Recognition based on Local Binary Pattern
IRJET- A Study on Face Recognition based on Local Binary PatternIRJET- A Study on Face Recognition based on Local Binary Pattern
IRJET- A Study on Face Recognition based on Local Binary PatternIRJET Journal
 
Facial Image Analysis for age and gender and
Facial Image Analysis for age and gender andFacial Image Analysis for age and gender and
Facial Image Analysis for age and gender andYuheng Wang
 
Volume 2-issue-6-2108-2113
Volume 2-issue-6-2108-2113Volume 2-issue-6-2108-2113
Volume 2-issue-6-2108-2113Editor IJARCET
 
Formalization & data abstraction during use case modeling in object oriented ...
Formalization & data abstraction during use case modeling in object oriented ...Formalization & data abstraction during use case modeling in object oriented ...
Formalization & data abstraction during use case modeling in object oriented ...csandit
 
Cartoon Based Image Retrieval : An Indexing Approach
Cartoon Based Image Retrieval : An Indexing ApproachCartoon Based Image Retrieval : An Indexing Approach
Cartoon Based Image Retrieval : An Indexing Approachmlaij
 
Automatic Identification of Sub Assembly in an Assembly
Automatic Identification of Sub Assembly in an AssemblyAutomatic Identification of Sub Assembly in an Assembly
Automatic Identification of Sub Assembly in an Assemblyishan kossambe
 
IRJET- Photo Optical Character Recognition Model
IRJET- Photo Optical Character Recognition ModelIRJET- Photo Optical Character Recognition Model
IRJET- Photo Optical Character Recognition ModelIRJET Journal
 
face recognition system using LBP
face recognition system using LBPface recognition system using LBP
face recognition system using LBPMarwan H. Noman
 
Knowledge extraction from numerical data an abc
Knowledge extraction from numerical data an abcKnowledge extraction from numerical data an abc
Knowledge extraction from numerical data an abcIAEME Publication
 
User Interactive Color Transformation between Images
User Interactive Color Transformation between ImagesUser Interactive Color Transformation between Images
User Interactive Color Transformation between ImagesIJMER
 
Face Recognition using PCA and Eigen Face Approach
Face Recognition using PCA and Eigen Face ApproachFace Recognition using PCA and Eigen Face Approach
Face Recognition using PCA and Eigen Face ApproachIRJET Journal
 
IRJET- Efficient Auto Annotation for Tag and Image based Searching Over Large...
IRJET- Efficient Auto Annotation for Tag and Image based Searching Over Large...IRJET- Efficient Auto Annotation for Tag and Image based Searching Over Large...
IRJET- Efficient Auto Annotation for Tag and Image based Searching Over Large...IRJET Journal
 
Face Recognition using Feature Descriptors and Classifiers
Face Recognition using Feature Descriptors and ClassifiersFace Recognition using Feature Descriptors and Classifiers
Face Recognition using Feature Descriptors and ClassifiersJournal For Research
 
Automatic ground truth generation for image sequences
Automatic ground truth generation for image sequencesAutomatic ground truth generation for image sequences
Automatic ground truth generation for image sequencesIAEME Publication
 
LATTICE-CELL : HYBRID APPROACH FOR TEXT CATEGORIZATION
LATTICE-CELL : HYBRID APPROACH FOR TEXT CATEGORIZATIONLATTICE-CELL : HYBRID APPROACH FOR TEXT CATEGORIZATION
LATTICE-CELL : HYBRID APPROACH FOR TEXT CATEGORIZATIONcsandit
 
Comparison of various Image Registration Techniques with the Proposed Hybrid ...
Comparison of various Image Registration Techniques with the Proposed Hybrid ...Comparison of various Image Registration Techniques with the Proposed Hybrid ...
Comparison of various Image Registration Techniques with the Proposed Hybrid ...idescitation
 

What's hot (17)

IRJET- A Study on Face Recognition based on Local Binary Pattern
IRJET- A Study on Face Recognition based on Local Binary PatternIRJET- A Study on Face Recognition based on Local Binary Pattern
IRJET- A Study on Face Recognition based on Local Binary Pattern
 
Facial Image Analysis for age and gender and
Facial Image Analysis for age and gender andFacial Image Analysis for age and gender and
Facial Image Analysis for age and gender and
 
Volume 2-issue-6-2108-2113
Volume 2-issue-6-2108-2113Volume 2-issue-6-2108-2113
Volume 2-issue-6-2108-2113
 
Y34147151
Y34147151Y34147151
Y34147151
 
Formalization & data abstraction during use case modeling in object oriented ...
Formalization & data abstraction during use case modeling in object oriented ...Formalization & data abstraction during use case modeling in object oriented ...
Formalization & data abstraction during use case modeling in object oriented ...
 
Cartoon Based Image Retrieval : An Indexing Approach
Cartoon Based Image Retrieval : An Indexing ApproachCartoon Based Image Retrieval : An Indexing Approach
Cartoon Based Image Retrieval : An Indexing Approach
 
Automatic Identification of Sub Assembly in an Assembly
Automatic Identification of Sub Assembly in an AssemblyAutomatic Identification of Sub Assembly in an Assembly
Automatic Identification of Sub Assembly in an Assembly
 
IRJET- Photo Optical Character Recognition Model
IRJET- Photo Optical Character Recognition ModelIRJET- Photo Optical Character Recognition Model
IRJET- Photo Optical Character Recognition Model
 
face recognition system using LBP
face recognition system using LBPface recognition system using LBP
face recognition system using LBP
 
Knowledge extraction from numerical data an abc
Knowledge extraction from numerical data an abcKnowledge extraction from numerical data an abc
Knowledge extraction from numerical data an abc
 
User Interactive Color Transformation between Images
User Interactive Color Transformation between ImagesUser Interactive Color Transformation between Images
User Interactive Color Transformation between Images
 
Face Recognition using PCA and Eigen Face Approach
Face Recognition using PCA and Eigen Face ApproachFace Recognition using PCA and Eigen Face Approach
Face Recognition using PCA and Eigen Face Approach
 
IRJET- Efficient Auto Annotation for Tag and Image based Searching Over Large...
IRJET- Efficient Auto Annotation for Tag and Image based Searching Over Large...IRJET- Efficient Auto Annotation for Tag and Image based Searching Over Large...
IRJET- Efficient Auto Annotation for Tag and Image based Searching Over Large...
 
Face Recognition using Feature Descriptors and Classifiers
Face Recognition using Feature Descriptors and ClassifiersFace Recognition using Feature Descriptors and Classifiers
Face Recognition using Feature Descriptors and Classifiers
 
Automatic ground truth generation for image sequences
Automatic ground truth generation for image sequencesAutomatic ground truth generation for image sequences
Automatic ground truth generation for image sequences
 
LATTICE-CELL : HYBRID APPROACH FOR TEXT CATEGORIZATION
LATTICE-CELL : HYBRID APPROACH FOR TEXT CATEGORIZATIONLATTICE-CELL : HYBRID APPROACH FOR TEXT CATEGORIZATION
LATTICE-CELL : HYBRID APPROACH FOR TEXT CATEGORIZATION
 
Comparison of various Image Registration Techniques with the Proposed Hybrid ...
Comparison of various Image Registration Techniques with the Proposed Hybrid ...Comparison of various Image Registration Techniques with the Proposed Hybrid ...
Comparison of various Image Registration Techniques with the Proposed Hybrid ...
 

Viewers also liked (20)

B011120510
B011120510B011120510
B011120510
 
D017162629
D017162629D017162629
D017162629
 
J010337176
J010337176J010337176
J010337176
 
Analysis of Ketoconazole and Piribedil Using Ion Selective Electrodes
Analysis of Ketoconazole and Piribedil Using Ion Selective ElectrodesAnalysis of Ketoconazole and Piribedil Using Ion Selective Electrodes
Analysis of Ketoconazole and Piribedil Using Ion Selective Electrodes
 
K010416167
K010416167K010416167
K010416167
 
C017130912
C017130912C017130912
C017130912
 
M017619194
M017619194M017619194
M017619194
 
H0213337
H0213337H0213337
H0213337
 
G017154852
G017154852G017154852
G017154852
 
I012314854
I012314854I012314854
I012314854
 
E1803053238
E1803053238E1803053238
E1803053238
 
F1102024349
F1102024349F1102024349
F1102024349
 
J1103046570
J1103046570J1103046570
J1103046570
 
B011120723
B011120723B011120723
B011120723
 
P01226101106
P01226101106P01226101106
P01226101106
 
F1802052830
F1802052830F1802052830
F1802052830
 
Derivational Error of Albert Einstein
Derivational Error of Albert EinsteinDerivational Error of Albert Einstein
Derivational Error of Albert Einstein
 
G017244250
G017244250G017244250
G017244250
 
A01260104
A01260104A01260104
A01260104
 
F017213747
F017213747F017213747
F017213747
 

Similar to F018113743

Component Diagram Example Templates
Component Diagram Example TemplatesComponent Diagram Example Templates
Component Diagram Example TemplatesCreately
 
Local Service Search Engine Management System LSSEMS
Local Service Search Engine Management System LSSEMSLocal Service Search Engine Management System LSSEMS
Local Service Search Engine Management System LSSEMSYogeshIJTSRD
 
Online eaxmination
Online eaxminationOnline eaxmination
Online eaxminationAditi_17
 
ppt-20.06.24.pptx ghyyuuuygrfggtyghffhhhh
ppt-20.06.24.pptx ghyyuuuygrfggtyghffhhhhppt-20.06.24.pptx ghyyuuuygrfggtyghffhhhh
ppt-20.06.24.pptx ghyyuuuygrfggtyghffhhhhshaikfahim2127
 
UML and Software Modeling Tools.pptx
UML and Software Modeling Tools.pptxUML and Software Modeling Tools.pptx
UML and Software Modeling Tools.pptxNwabueze Obioma
 
Report on jal app
Report on jal appReport on jal app
Report on jal appOmkar Rane
 
IRJET- Computerized Attendance System using Face Recognition
IRJET- Computerized Attendance System using Face RecognitionIRJET- Computerized Attendance System using Face Recognition
IRJET- Computerized Attendance System using Face RecognitionIRJET Journal
 
IRJET- Computerized Attendance System using Face Recognition
IRJET- Computerized Attendance System using Face RecognitionIRJET- Computerized Attendance System using Face Recognition
IRJET- Computerized Attendance System using Face RecognitionIRJET Journal
 
Automatic Graphical Design Generator
Automatic Graphical Design GeneratorAutomatic Graphical Design Generator
Automatic Graphical Design GeneratorIRJET Journal
 
SOURCE CODE MANAGEMENT SYSTEM (GITHUB)
SOURCE CODE MANAGEMENT SYSTEM (GITHUB)SOURCE CODE MANAGEMENT SYSTEM (GITHUB)
SOURCE CODE MANAGEMENT SYSTEM (GITHUB)Gracy Joseph
 
Software Engineering Tools and Practices.pdf
Software Engineering Tools and Practices.pdfSoftware Engineering Tools and Practices.pdf
Software Engineering Tools and Practices.pdfMeagGhn
 
online national polling
online national pollingonline national polling
online national pollingKasi Annapurna
 
Neural Net: Machine Learning Web Application
Neural Net: Machine Learning Web ApplicationNeural Net: Machine Learning Web Application
Neural Net: Machine Learning Web ApplicationIRJET Journal
 
Student Attendance Using Face Recognition
Student Attendance Using Face RecognitionStudent Attendance Using Face Recognition
Student Attendance Using Face RecognitionIRJET Journal
 
Smart Doorbell System Based on Face Recognition
Smart Doorbell System Based on Face RecognitionSmart Doorbell System Based on Face Recognition
Smart Doorbell System Based on Face RecognitionIRJET Journal
 
GENERATION OF DATABASE AND GUI IN SHAPE MATCHING TECHNIQUE | J4RV3I12001
GENERATION OF DATABASE AND GUI IN SHAPE MATCHING TECHNIQUE | J4RV3I12001GENERATION OF DATABASE AND GUI IN SHAPE MATCHING TECHNIQUE | J4RV3I12001
GENERATION OF DATABASE AND GUI IN SHAPE MATCHING TECHNIQUE | J4RV3I12001Journal For Research
 
A Review on data visualization tools used for Big Data
A Review on data visualization tools used for Big DataA Review on data visualization tools used for Big Data
A Review on data visualization tools used for Big DataIRJET Journal
 
IRJET- 3-D Face Image Identification from Video Streaming using Map Reduc...
IRJET-  	  3-D Face Image Identification from Video Streaming using Map Reduc...IRJET-  	  3-D Face Image Identification from Video Streaming using Map Reduc...
IRJET- 3-D Face Image Identification from Video Streaming using Map Reduc...IRJET Journal
 
Review on Automation Tool for ERD Normalization
Review on Automation Tool for ERD NormalizationReview on Automation Tool for ERD Normalization
Review on Automation Tool for ERD NormalizationIRJET Journal
 

Similar to F018113743 (20)

Component Diagram Example Templates
Component Diagram Example TemplatesComponent Diagram Example Templates
Component Diagram Example Templates
 
Local Service Search Engine Management System LSSEMS
Local Service Search Engine Management System LSSEMSLocal Service Search Engine Management System LSSEMS
Local Service Search Engine Management System LSSEMS
 
Online eaxmination
Online eaxminationOnline eaxmination
Online eaxmination
 
ppt-20.06.24.pptx ghyyuuuygrfggtyghffhhhh
ppt-20.06.24.pptx ghyyuuuygrfggtyghffhhhhppt-20.06.24.pptx ghyyuuuygrfggtyghffhhhh
ppt-20.06.24.pptx ghyyuuuygrfggtyghffhhhh
 
UML and Software Modeling Tools.pptx
UML and Software Modeling Tools.pptxUML and Software Modeling Tools.pptx
UML and Software Modeling Tools.pptx
 
Report on jal app
Report on jal appReport on jal app
Report on jal app
 
IRJET- Computerized Attendance System using Face Recognition
IRJET- Computerized Attendance System using Face RecognitionIRJET- Computerized Attendance System using Face Recognition
IRJET- Computerized Attendance System using Face Recognition
 
IRJET- Computerized Attendance System using Face Recognition
IRJET- Computerized Attendance System using Face RecognitionIRJET- Computerized Attendance System using Face Recognition
IRJET- Computerized Attendance System using Face Recognition
 
Automatic Graphical Design Generator
Automatic Graphical Design GeneratorAutomatic Graphical Design Generator
Automatic Graphical Design Generator
 
SOURCE CODE MANAGEMENT SYSTEM (GITHUB)
SOURCE CODE MANAGEMENT SYSTEM (GITHUB)SOURCE CODE MANAGEMENT SYSTEM (GITHUB)
SOURCE CODE MANAGEMENT SYSTEM (GITHUB)
 
Software Engineering Tools and Practices.pdf
Software Engineering Tools and Practices.pdfSoftware Engineering Tools and Practices.pdf
Software Engineering Tools and Practices.pdf
 
online national polling
online national pollingonline national polling
online national polling
 
Neural Net: Machine Learning Web Application
Neural Net: Machine Learning Web ApplicationNeural Net: Machine Learning Web Application
Neural Net: Machine Learning Web Application
 
Student Attendance Using Face Recognition
Student Attendance Using Face RecognitionStudent Attendance Using Face Recognition
Student Attendance Using Face Recognition
 
Smart Doorbell System Based on Face Recognition
Smart Doorbell System Based on Face RecognitionSmart Doorbell System Based on Face Recognition
Smart Doorbell System Based on Face Recognition
 
Uml
UmlUml
Uml
 
GENERATION OF DATABASE AND GUI IN SHAPE MATCHING TECHNIQUE | J4RV3I12001
GENERATION OF DATABASE AND GUI IN SHAPE MATCHING TECHNIQUE | J4RV3I12001GENERATION OF DATABASE AND GUI IN SHAPE MATCHING TECHNIQUE | J4RV3I12001
GENERATION OF DATABASE AND GUI IN SHAPE MATCHING TECHNIQUE | J4RV3I12001
 
A Review on data visualization tools used for Big Data
A Review on data visualization tools used for Big DataA Review on data visualization tools used for Big Data
A Review on data visualization tools used for Big Data
 
IRJET- 3-D Face Image Identification from Video Streaming using Map Reduc...
IRJET-  	  3-D Face Image Identification from Video Streaming using Map Reduc...IRJET-  	  3-D Face Image Identification from Video Streaming using Map Reduc...
IRJET- 3-D Face Image Identification from Video Streaming using Map Reduc...
 
Review on Automation Tool for ERD Normalization
Review on Automation Tool for ERD NormalizationReview on Automation Tool for ERD Normalization
Review on Automation Tool for ERD Normalization
 

More from IOSR Journals (20)

A011140104
A011140104A011140104
A011140104
 
M0111397100
M0111397100M0111397100
M0111397100
 
L011138596
L011138596L011138596
L011138596
 
K011138084
K011138084K011138084
K011138084
 
J011137479
J011137479J011137479
J011137479
 
I011136673
I011136673I011136673
I011136673
 
G011134454
G011134454G011134454
G011134454
 
H011135565
H011135565H011135565
H011135565
 
F011134043
F011134043F011134043
F011134043
 
E011133639
E011133639E011133639
E011133639
 
D011132635
D011132635D011132635
D011132635
 
C011131925
C011131925C011131925
C011131925
 
B011130918
B011130918B011130918
B011130918
 
A011130108
A011130108A011130108
A011130108
 
I011125160
I011125160I011125160
I011125160
 
H011124050
H011124050H011124050
H011124050
 
G011123539
G011123539G011123539
G011123539
 
F011123134
F011123134F011123134
F011123134
 
E011122530
E011122530E011122530
E011122530
 
D011121524
D011121524D011121524
D011121524
 

Recently uploaded

08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking MenDelhi Call girls
 
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j
 
Unblocking The Main Thread Solving ANRs and Frozen Frames
Unblocking The Main Thread Solving ANRs and Frozen FramesUnblocking The Main Thread Solving ANRs and Frozen Frames
Unblocking The Main Thread Solving ANRs and Frozen FramesSinan KOZAK
 
Top 5 Benefits OF Using Muvi Live Paywall For Live Streams
Top 5 Benefits OF Using Muvi Live Paywall For Live StreamsTop 5 Benefits OF Using Muvi Live Paywall For Live Streams
Top 5 Benefits OF Using Muvi Live Paywall For Live StreamsRoshan Dwivedi
 
Developing An App To Navigate The Roads of Brazil
Developing An App To Navigate The Roads of BrazilDeveloping An App To Navigate The Roads of Brazil
Developing An App To Navigate The Roads of BrazilV3cube
 
Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024The Digital Insurer
 
Handwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsHandwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsMaria Levchenko
 
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Drew Madelung
 
Factors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptxFactors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptxKatpro Technologies
 
The Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxThe Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxMalak Abu Hammad
 
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationFrom Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationSafe Software
 
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...Neo4j
 
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...Igalia
 
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...apidays
 
Automating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps ScriptAutomating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps Scriptwesley chun
 
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...Miguel Araújo
 
CNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of ServiceCNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of Servicegiselly40
 
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptxHampshireHUG
 
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking MenDelhi Call girls
 
A Call to Action for Generative AI in 2024
A Call to Action for Generative AI in 2024A Call to Action for Generative AI in 2024
A Call to Action for Generative AI in 2024Results
 

Recently uploaded (20)

08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
 
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
 
Unblocking The Main Thread Solving ANRs and Frozen Frames
Unblocking The Main Thread Solving ANRs and Frozen FramesUnblocking The Main Thread Solving ANRs and Frozen Frames
Unblocking The Main Thread Solving ANRs and Frozen Frames
 
Top 5 Benefits OF Using Muvi Live Paywall For Live Streams
Top 5 Benefits OF Using Muvi Live Paywall For Live StreamsTop 5 Benefits OF Using Muvi Live Paywall For Live Streams
Top 5 Benefits OF Using Muvi Live Paywall For Live Streams
 
Developing An App To Navigate The Roads of Brazil
Developing An App To Navigate The Roads of BrazilDeveloping An App To Navigate The Roads of Brazil
Developing An App To Navigate The Roads of Brazil
 
Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024
 
Handwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsHandwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed texts
 
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
 
Factors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptxFactors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptx
 
The Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxThe Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptx
 
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationFrom Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
 
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
 
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
 
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
 
Automating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps ScriptAutomating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps Script
 
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
 
CNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of ServiceCNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of Service
 
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
 
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
 
A Call to Action for Generative AI in 2024
A Call to Action for Generative AI in 2024A Call to Action for Generative AI in 2024
A Call to Action for Generative AI in 2024
 

F018113743

  • 1. IOSR Journal of Computer Engineering (IOSR-JCE) e-ISSN: 2278-0661,p-ISSN: 2278-8727, Volume 18, Issue 1, Ver. I (Jan – Feb. 2016), PP 37-43 www.iosrjournals.org DOI: 10.9790/0661-18113743 www.iosrjournals.org 37 | Page Towards Automated Generation of ER-Diagram using a Web Based Approach Amol V. Khaire1 , Pramod B. Mali2 1 PG Student, Department of Computer Engineering, Smt. Kashibai Navale College of Engineering, Vadgaon Bk, Pune, India 2 Assistant Professor, Department of Computer Engineering, Smt. Kashibai Navale College of Engineering, Vadgaon Bk, Pune, India Abstract : Diagrams plays an important role in the software development process. Drawing the diagrams manually is the time consuming task, so there are many tools to draw and modify the diagram. From all the diagrams ER (Entity Relationship) Diagram plays an important role in the software development process in Computer Engineering. This paper will describe the existing tools and presents a Web Application to generate the Entity Relationship Diagram automatically. This Web Application will allow us to generate Entity Relationship Diagram automatically by a form filling method which will take the Entity, Attribute and Relationship as an input and gives the Entity Relationship Diagram as output automatically. Keywords - Automated ER-Diagram, Entity Relationship Diagram, Software Development Process, Web Application I. INTRODUCTION There are numerous Diagrams like block diagrams, organizational chart for showing the hierarchical structure, network diagram of an association, Pie Chart, Flow Chart, ER-Diagram and so forth. In any case, out of every one of these Diagrams ER-Diagram is critical in the programming development process. In today's business world, databases are almost significant, as they describe information about an organization and entity relationship modeling is by a wide margin the most well-known approach to express the expository consequence of an early stage in the creation of the new database [1]. In this paper, we are going to see the distinction between the ER-Diagram creating tools which is a manual procedure, additionally require the lots of knowledge about tools and a web Application that we are going to create. Presently there are different tools to draw the diagram. These tools are not at risk for automatic generation of ER-Diagram (Entity Relationship graph). These tools provide the platform for the user to represent the ER-diagram using various symbols. Currently used tools for creation of ER-diagram are Edraw [7], DIA [8] and so forth. These tools are producing the Entity Relationship Diagram manually. This infer to requirement of dragging and dropping the items which are required to draw the Entity Relationship Diagram. It should to be noticed that there are numerous representations of ER-Diagram for the same problem. We additionally plan to implement the web Application in the three stages Step1:- Taking the input from the user, i.e. Entity, Attribute and Relationships Step2:- Providing input to a web form. Step3:- Generate and Store the ER-Diagram. DIA [7] and Edraw [8] is a manual tool to produce ER-Diagram. Paper [1] has not more concentrate on ER-Diagram, paper [2] has not Clear thought regarding the how to produce an ER-diagram naturally, paper [3] have the troublesome procedure for creating ER-Diagram automatically, so we are developing the Web application which is generating the Entity Relationship Diagram automatically. As this process is automatic this can be very useful for the user. II. LITERATURE SURVEY ADG (Auto-Diagram generator) tool is used to create the Flow Chart, Block Diagram and Entity Relationship Diagram by form filling and text selection method [1]. Form filling strategy used is one of the best methodologies for a novice user to determine the diagram prerequisites. The diagram generator and editor is the principle part of this tool. DeZign tool is utilized for generation of a diagram [2]. DeZign tool creates the Extended Entity Relationship Diagram and this is utilizing the form filling system as like the ADG (auto graph generator) tool. DeZign utilize the three modules to create the Diagram. DeZign device utilizes a Simple English explanation as information and gives the Entity Relationship Diagram as a yield. Paper [3] Explains about an ABCM (Association based theoretical model) and how the ABCM utilizes a connection Adaptive way to deal with creating the Entity Relationship chart. Before creating the ER diagram a graphical tool called Association based theoretical model is utilized to discover a relationship between a two or more objects
  • 2. Towards Automated Generation of ER-Diagram using a Web Based Approach DOI: 10.9790/0661-18113743 www.iosrjournals.org 38 | Page described in the business depictions. The ABCM can deal with a three or more objects and also two ones in a breath. AER (Articulated Entity Relationship) is created from the Entity-Relationship diagram [5]. The AER is an expansion to the ER-graph. In the AER, diagram is produced automatically, but the ER-diagram is taken manually. NLP (natural language processing) is used for producing the Entity-Relationship diagram [6]. Heuristic methodology is utilized for producing the Entity Relationship diagram. The semantic Heuristics will be utilized to decide the Entity, Attribute and Relationships from a database specification. Heuristics are a superior methodology however the Diagram generation process is complicated because of this. Syntactic Heuristics are executed in the ER-converter. Diagram generation algorithms are given in [4]. Building block diagrams, graphical objects, diagram resizing and graph altering algorithms are depicted. However, the procedure utilized is manual. Table 1 demonstrates the correlation between the distinctive tools like ADG, ABCS and DeZign. Table 1 additionally indicates how these devices are ideal to produce the Entity relationship graph. Right now there are numerous tools existing for the generation of an ER-diagram (entity relationship diagram). These tools are DIA [7], Edraw [8] and so on. DIA device is utilized to create the diagrams like stream flow chart, block diagram, ER-Diagram and so on. In any case, before drawing the diagram we need to first install that tool on our machine and should have knowledge about the DIA tool. In the DIA process, drawing diagram is manual. Thus, diagram generation process in DIA is tedious. Edraw is another tool as like DIA which additionally utilizes the manual procedure to draw the diagram. Tool Name Survey Details Findings ADG Tool[1] This explains about Automating diagram process and for atomization they use ADG tool which uses the form filling method. Tool explains about atomization of other diagrams and does not focus on ER-diagram. DeZign Tool[2] This explains about automating diagram process and use DeZign tool to generate the Entity Relationship Diagram. Clear thought regarding how to produce ER-diagram automatically is not clarified. ABCS(Association-Based Conceptual Based Systems) Tool[3] For ER-diagram generation process uses ABCS(Association-Based Conceptual Based Systems).This uses the Context Adaptive approach to generate the ER- Diagram Difficult process for generating ER-diagram automatically. Table 1:- Comparison between Automated Tools III. PROPOSED SYSTEM Proposed system discusses about system architecture and mathematical model of automated ER-Diagram generation. 3.1 System Architecture System architecture indicates how we are developing the web Application to produce the Automated Entity Relationship Diagram. Figure 1 demonstrates a System Architecture for producing the Entity Relationship Diagram automatically. As the architecture is a web based so, we need to build up a web application. In Automated ER-Diagram Generation we have the web page which will take the Entity, Attribute, Relationships as data and giving the ER-Diagram as output. A Proposed plan for an automated ER-Diagram is partitioned into the 3 modules. Module1: Accepting Entity, Attribute and Relationships. Module2: Generating ER-Diagram automatically. Module3: Storing ER-Diagram onto the device. In the module 1, we are accepting the Entity details, Attribute details and Relationship details from the user through the user interface. Entity details contain the quantity of Entities, name of every Entity and type of each entity. Attribute details contains the quantity of Attributes for respective entity, the name of each Attribute, the type of each attribute. Relationship details contain the name of the relationship between any two entities. As this procedure is on the web so in the wake of giving the data this data is sent to the server. At the point when
  • 3. Towards Automated Generation of ER-Diagram using a Web Based Approach DOI: 10.9790/0661-18113743 www.iosrjournals.org 39 | Page data goes to a server then this data is saved into a database. This data will be given in the following module to create the output. In module 2, we are giving Entity detail, attribute details & Relationship details as input to this module and generating the ER-Diagram automatically. In module 3 we are taking the ER-Diagram which is created by the Module 2 and this Diagram is saved into the format which a user is comfortable. After saving a file in this format the file is stored onto a storage device and then provided to the user. The User needs to give all the data to create the ER-Diagram automatically. Figure 1 shows the proposed design diagram which takes the input as an Entity, Attribute & Relationships. Then this input information is provided on the web page which generates ER-Diagram automatically. Figure 1 shows this basic system architecture to generate the ER-Diagram. Arrows in the diagram show the input and output to and from the web application. Initially a user gives an input which is provided to the webpage and these web pages will give the output as the ER-Diagram as shown in the Diagram. Figure 1 also shows an IIS (internet information server) Server. The ISS sever is the server on which our automated ER-Diagram generation web application is running. When contrasted with the past devices this Web Application is the better way to deal with produce ER-diagram furthermore as these are accessible on the web so it is easy to use for the User. Fig. 3.1: System Architecture for Automated ER-Diagram Generation. 3.2. Mathematical Model Set Theory: Let S be the set then, S= {EN, AT, RS} Where, EN=set of entities AT=set of attributes RS=set of relationships and EN, AT and RS are represented as EN= {E1, E2, E3,……….En} AT= {A11, A12, A13,………. A1n, A21, A22, A23,………. A2n, An1, An2, An3,…...….. Ann} RS= {R1, R2, R3…. Rn}
  • 4. Towards Automated Generation of ER-Diagram using a Web Based Approach DOI: 10.9790/0661-18113743 www.iosrjournals.org 40 | Page IV. EXPERIMENTAL RESULTS This section discusses about how ER-diagram is generated automatically. Screenshot 4.1, shows the Entity filter details for three levels, i.e. low, middle and expert. Screenshot 4.1: Entity filters Details. Screenshot 4.2, shows the Attribute filter details for three levels, i.e. Low, Middle and Expert. Screenshot 4.3, shows the Relationship filter details for three levels, i.e. Low, Middle and Expert. Screenshot 4.4, shows the low level ER-diagram which is generated by filtering Entity, Attribute and Relationship. Screenshot 4.5, shows the Middle level ER-diagram which is generated by filtering Entity, Attribute and Relationship. Screenshot 6 shows the Expert level ER-diagram which is generated by filtering Entity, Attribute and Relationship.
  • 5. Towards Automated Generation of ER-Diagram using a Web Based Approach DOI: 10.9790/0661-18113743 www.iosrjournals.org 41 | Page Screenshot 4.2: Attribute filters Details. Screenshot 4.3: Relationship filters Details.
  • 6. Towards Automated Generation of ER-Diagram using a Web Based Approach DOI: 10.9790/0661-18113743 www.iosrjournals.org 42 | Page Screenshot 4.4: Low level ER-Diagram. Screenshot 4.5: Medium level E-R Diagram.
  • 7. Towards Automated Generation of ER-Diagram using a Web Based Approach DOI: 10.9790/0661-18113743 www.iosrjournals.org 43 | Page Screenshot 4.6: Expert level E-R Diagram. V. CONCLUSION A Web Application for Automated generation of ER-Diagram provides a way to generate Automated ER- diagrams, which makes it usable for a wide range of users. This Web Application is user friendly and rather than drag and drop approach it uses an automated approach to generate the diagram. A user does not require more knowledge to generate the diagrams as compared to other available tools. A Web Based approach towards Automated ER-Diagram generation can be extended to generate the Extended Entity Relationship Diagram (EED) automatically by providing input as an attribute, entity and so forth. In future we can also extend this for generating all the UML diagrams like Use case diagram, Data Flow diagram, Class Diagram and so forth. REFERENCES [1] Tabinda Sarwar, Uzma Arif, Wajiha Habib, Samna Zehra, “Automating The Diagram Generation Process”, International Journal of Scientific and Engineering Research Volume 2, Issue 7, July-2011 [2] Dr. Muhammad Shahbaz, Dr. Syed Ahsan, ammad Shaheen, Rao Muhammad Adeel Nawab, Syed Athar Masood, University of Engineering & Technology Lahore, Punjab Pakistan, "Automatic Generation of Extended ER Diagram Using Natural Language Processing”, Journal of American Science, 2011 [3] Sangwon Lee, Namgyu Kim and Songchun Moon, Department of Management Engineering, Korea Advanced Institute of Science and Technology, Seoul130-722, Korea, “Context Adaptive Approach for Automated Entity Relationship Modeling”, journal of information science and engineering 26, 2229-2247 (2010). [4] Tabinda Sarwar, Uzma Arif, Wajiha Habib Samana Zehra, “An Efficient and Simplest Algorithm for Generating Diagrams”, International Journal of Scientific & Engineering Research Volume 2, Issue 7, July-2011,ISSN 2229-5518 [5] P. S. Dhabe, Dr. M. S. Patwardhan, Asavari A. Deshpande, M. L. Dhore, B.V. Barbadekar and H. K. Abhyankar, Department of Computer Engineering, Vishwakarma Institute of Technology, Pune-411037, Maharashtra State, India, “Articulated Entity Relationship Diagram for Complete Automation of Relational Database Normalization”, International Journal of Database Management System, Volume 2, Num 2 [6] N. Omar, P. Hanna and P. Mc Kevitt, “Semantic Analysis in the Automation of ER Modelling through Natural Language Processing” [7] Edraw Max. Available:http://www.edrawsoft.com [8] Dia. Available: http://www.diahome.org