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Project Report (Paper-410)

B. Sc (H) Computer Science (IV Semester)Area: Software Engineering

ONLINE VOTING SYSTEMFOR COLLEGE ELECTIONS

Ram Lal Anand College,Benito Juarez Rd, South Campus, New Delhi

University of Delhi

Submitted By: Under SupervisionShubham Nauriyal Dr. Vandana GandotraKunal Sharma (Associate Professor)

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CERTIFICATE

This is to certify that the project entitled, “ONLINE

VOTING SYSTEM FOR COLLEGE ELECTIONS”

has been done by:-

Kunal Sharma and Shubham Nauriyal of Bachelor of

Computer Science (Hons.) during semester IV from Ram Lal

Anand College, University of Delhi under the supervision of

Dr. Vandana Gandotra.

Dr. Vandana Gandotra

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ACKNOWLEDGEMENT

The Project was jointly undertaken by Shubham Nauriyal and Kunal

Sharma as their 4th Semester Software Engineering Project, under the

able guidance and supervision of Dr. Vandana Gandotra. Our primary

thanks goes to her, who poured over every inch of our project with

painstaking attention and helped us throughout the working of the

project. It’s our privilege to acknowledge our deepest sense of gratitude

to her for her inspiration which has helped us immensely. We are

extremely grateful to her for her unstilted support and encouragement in

the preparation of this project.

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TABLE OF CONTENTS

Acknowledgement

1. INTRODUCTION

1.1 Problem statement 1.2 Process model

2. REQUIREMENT ANALYSIS

2.1 Data Flow Diagram (DFD) 2.2 Data Dictionary (DD)

3. PROJECT MANAGEMENT

3.1 Function Points 3.2 Effort Estimation 3.3 Schedule Estimation 3.4 Risk Table 3.5 Timeline Chart

4. DESIGN ENGINEERING

4.1 Architectural Design 4.2 Data Design 4.3 Component Level Design

5. SOFTWARE TESTING

5.1 Computing Basis Path Testing

6. REFERENCES

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1. INTRODUCTION

“ONLINE VOTING SYSTEM FOR COLLEGE ELECTIONS” is an online voting technique. In which student can give his\her vote online without going to the college on the day of elections. This will surely consume less time as whole the day is being consumed on the day of elections. There is a DATABASE which is maintained in which all the names of students with complete information are stored. Each student is provided by a “User ID” and “Password” by using that ID and PASSWORD he\she can use his\her vote. The scope of this project will be that it will surely increase the voting percentage in university and college elections. Online Voting System will be fast enough to calculate the results and reduce the human efforts, as all the things will be automated.

1.1 Problem statement

As the statistics shows that the percentage of polling on the day of elections is not satisfactory as majority of students are not coming to vote and thinks is just as a wastage of time.The manual voting system takes long time as there is a lot of paper work first and then human effort is also there for counting of the votes.Manual voting consumes almost 4-6 hrs (approx.) of every voter which is surely a headache.The voting of the college elections will be done online such that there is no need to come at the college on the time of elections and the student can vote from the home or from any other place.A USER ID and PASSWORD will be provided to every student of the college, so that on the time of elections they can easily login on the election link and can use his/her vote.

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1.2 Process Model

A process model for software engineering is choosen based on the nature of the project and application, the methods and tools to be used, and the controls and deliverables that are required.The model is used to build the “ONLINE VOTING SYSTEM”software is “The Prototyping Model”. The prototyping paradigm is: - “Water fall model”

Fig.1.2 Water fall Model

The water fall model is a software development model in which a systems development is viewed as flowing downwards through the phases of the system development process. The waterfall methodology is powerful, précised, and thorough. It has a number of phases that have to be implemented in a sequential manner.The phases which come under the waterfall model are as follows:-

1.Requirement Analysis2.Design3.Implementation4.Testing5.Maintenance

Advantages:

1.Good for large projects2.Waterfall suits a principled approach to design3.Waterfall divides the project into manageable areas4.Waterfall separates the logical and physical

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2. REQUIREMENT ANALYSIS

The basic function of requirement analysis is that it translates the ideas in the mind of the clients into a formal document. Thus the output of this phase is a set of precisely specified requirements which are complete and consistent. This document is called Software Requirement Specification. In order to provide the user with a feeling of community, the following requirement should be taken care:

Each user will have to create their own profile that they can log into each time they visit the site.

If the user does not create or log in to an account they will only be able to browse questions on the site, they will not be able to use any of the sites other functionalities.

In order to create an account the user must have a college email address (verified by server).

Once they create an account the user will be able to Log in and out of the system, Upload a picture, choose their status (i.e. Student, TA, Professor).

Upload information about themselves (name, AIM, college email, hobbies, etc.) Select a college and area of study. View and send private messages to other users through a custom messaging client.

Questions and Answer functionality: Users will be able to post new questions, able to answer questions and post sources for their answers, search for questions containing key words, thumbs up and thumbs down questions and responses Users can bookmark questions, send questions to friends.

2.1 Data Flow Diagram (DFD)

A data flow diagram is a graphical representation that depicts information flow and the transforms that are applied as data move from input to output.The basic form of a data flow diagram, also known as a data flow graph or a bubble chart, The data flow diagram may be used to represent a system or software at any level of abstraction.As information moves through software, it is modified by a series of transformations. A data flow diagram is a graphical representation that depicts information flow and the transforms that are applied as data move from input to output. The basic form of a data flow diagram, also known as a data flow graph or a bubble chart. DFD is an abstract description of the system. The data flow diagram may be used to represent a system or software at any level of abstraction.DFDs may be partitioned into levels that represent increasing information flow and functional detail. Therefore, the DFD provides a mechanism for functional modeling as well as information flow modeling. DFDs are very useful in understanding a system and can be effectively used during analysis.DFDs can be hierarchically organized, which helps in progressively partitioning and analyzing large systems. Such DFDs are called leveled DFDs. Context diagram is a diagram in which the entire system is treated as a single process and all its inputs, outputs, sinks, and sources are identified and shown.

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Fig.2.1 (a) level 0 DFD

Fig.2.1 (b) level 1 DFD

2.2 Data Dictionary (DD)

The data dictionary is an organized listing of all data elements that are pertinent to the system, with precise, rigorous definitions so that both user and system analyst will have a common understanding of inputs, outputs, components of stores and intermediate calculations.Symbols used ‘+’ represents composition, ‘|’ means selection and ‘*’ means repetition.

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Username = Name|DigitName = First + Middle + LastFirst = [a|b|c_ _ _ _ _ _ _|z|A|B|C_ _ _ _ _ _|Z]*Middle = [a|b|c_ _ _ _ _ _ _|z|A|B|C_ _ _ _ _ _|Z]*Last = [a|b|c_ _ _ _ _ _ _|z|A|B|C_ _ _ _ _ _|Z]*Digit=[0|1|2|3|_ _ _ _ _ |9]*Successful = DoneUnsuccessful = Not DoneAuthenticated = DoneStatus = Yes/NoReceipt = [Code] + digit + digit + digit + digit + NamePassword = [word] | digit

Word = [0|1|2|3|_ _ _ _ _|9]*

Fig.2.2 Data Dictionary (DD)

3. PROJECT MANAGEMENT

Project management involves the planning, monitoring, and control of the people, process, and events that occur as software evolves from a preliminary concept to an operational implementation. Project managers plan, monitor, and control the work of a team of software engineers. Effective software project management focuses on the four P‟s: people, product, process, and project.

3.1 Function Points

Function-oriented software metrics use a measure of the functionality delivered by the application as a normalization value. Since, “functionality” cannot be measured directly; it must be derived indirectly using other direct measures. Function points are computed by completing the table 4.1. Five information domain characteristics are determined and counts are provided in the appropriate table location. Information domain values are defined in the following manner:

Number of user inputs: Each user input that provides distinct application oriented data to the software is counted. Inputs should be distinguished from inquiries, which are counted separately.

Number of user outputs: Each user output that provides application oriented information to the user is counted. In this context output refers to reports, screens, error messages, etc. Individual data

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items within a report are not counted separately.

Number of user inquiries: An inquiry is defined as an on-line input that results in the generation of some immediate software response in the form of an on-line output. Each distinct inquiry is counted.

Number of files: Each logical master file (i.e., a logical grouping of data that may be one part of a large database or a separate file) is counted.

Number of external interfaces: All machine readable interfaces (e.g., data files on storage media) that are used to transmit information to another system are counted.

Table 3.1 Weighting factor

Measurement factors Count Simple Average Complex

Number of user inputs 2 3 4(2) 6 8

Number of user output 2 4 5(2) 7 10

Number of user inquiries 3 3 4(3) 6 12

Number of internal logical files 1 7 10(1) 15 10

Number of external interface files 2 5 7(2) 10 14

Count total 54

The Fi (i = 1 to 14) are "Complexity Adjustment Values" based on responses to the following questions:

1. Does the system require reliable backup and recovery? 2. Are data communications required?3. Are there distributed processing functions?4. Is performance critical?5. Will the system run in an existing, heavily utilized operational environment?6. Does the system require on-line data entry? 7. Does the on-line data entry require the input transaction to be built over multiple?8. Are the master files updated on-line?9. Are the inputs, outputs, files, or inquiries complex?10. Is the internal processing complex?11. Is the code designed to be reusable? 12. Are conversion and installation included in the design?13. Is the system designed for multiple installations in different organizations?

55344535112355

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14. Is the application designed to facilitate change and ease of use by the user?

Once these data have been collected, a complexity value is associated with each count. Organizations that use function point methods develop criteria for determining whether a particular entry is simple, average, or complex. To compute function points (FP), the following relationship is used:FP = count total *[0.65 + 0.01 *Σ (Fi)]= 54*(0.65 + 0.01*51)=54*1.16=62 (approx.)Where count total is the sum of all FP entries obtained from Figure.

3.2 ESTIMATING EFFORTS

Barry Boehm introduced a hierarchy of software estimation models bearing the name COCOMO, for COnstructive COst MOdel. The original COCOMO model became one of the most widely used and discussed software cost estimation models in the industry. The COCOMO II application composition model uses object points.The object point is an indirect software measure that is computed using counts of the no. of screens (user interface), reports and components likely to be required to build the application. Each object instance is classified into one of three complexity levels using criteria suggested by Boehm.Once complexity is determined, the number of screens, reports, and components are weighted. The object point count is then determined by multiplying the original number of object instances by the weighting factor in and summing to obtain a total object point count. When component-based development or general software reuse is to be applied, the percent of reuse (%reuse) is estimated and the object point count is adjusted:NOP = (object points) x [(100 -%reuse)/100],where NOP is defined as new object points.To derive an estimate of effort based on the computed NOP value, “productivity rate” must be derived.PROD = NOP/person-monthTable 3.1 presents the productivity rate for different levels of developer experience and development environment maturity. Once the productivity rate has been determined, an estimate of project effort can be derived asEstimated effort = NOP/PROD

Object type No. of objects Complexity Weight Count

Simple Medium Difficult Screen 4 1(2) 2(2) 3(1) 7

Report 2 2(2) 5(1) 8(0) 9

3GL component 2 10(2) 20Object points sum 36

Table 3.2 Estimating object points

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Data used in estimating effort are:(1) Object points is 36(taken from table 3.2)(2) Estimated reuse is 36%(3) Prod is 13 (average value taken)NOP = Object points *[(100-reuse%)/100]= 36*[(100-35)/100]= 24ESTIMATED EFFORT = NOP/PROD= 24/13= 2 person-monthsHence estimated effort of the project is 2 person-months.

3.3 ESTIMATING SCHEDULEPutnam and Myers suggest a set of equations derived from the software equation. Minimum development time is defined as

tmin=8.14¿ in months for tmin> 6 months

Since project’s time period is less than 6 months, the above equation cannot be applied.

An estimation model of the form:

E = [LOC−B .333

P ]3

×(1

t 4 ) (equation 1)

where E = effort in person-months or person-years

t = project duration in months or years

B = “special skills factor”

P = “productivity parameter”

Calculating development time for project, using equation 1 and effort calculated in section 3.2

2 = [1000−0.01.333

8000 ]3

×(1

t 4 )

t4 =0.06

Hence estimated schedule of the project is 0.06 months.

3.4 RISK TABLE

A table provides a project manager with a simple technique for risk production. A risk table is sorted by probability and impact to rank risks. A project team begins by listing all risks in the 1st column of the table. This can accomplished with the help of the risk item checklist referenced. Each risk is categorized in the 2nd column. The probability of occurrence of each risk is entered in the next column of the table.Next, the impact of each risk is assessed. Each risk component is assessed using the characterization presented and an impact category is determine. The categories for each of the four

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risk components-performance, support, cost and schedule-are averaged to determine an overall impact value.Once the first four columns of the risk table have been completed, the table is sorted by probability and by impact. High-probability, high-impact, risk-impact risks percolate to the top of the table and low-probability risks drop to the bottom. Table 3.4 Risk Table

Risk Category Probability Impact RMMM

Hacker attack TE 30% 1 Appoint experts team to overcome the situation.

Environmental factors

BU 30% 2 Replication to different data centres.

Delivery deadline will be tightened

BU 50% 2 Increase the amount of resources available.

Staff inexperienced

ST 30% 2 Meet with experienced developer and experts of projects.

Size estimates may be significantly low

PS 60% 2 Check the modules and revise the algorithm

Staff turnover will be high

ST 60% 2 Meet with current staff to determine causes for turnover.Assign the backup staff member for every critical technologist.

Less reuse than planned

PS 70% 2 Revise the components than to be used.

Performance TE 20% 2 Consult the experienced software makers.

Unavailability of team members

BU 20% 3 Ensure that there is always an emergency person who can always take over the task assign is not available.

Reviews may not be conducted regularly

BU 30% 3 Set dates for reviews for each documentation.

Impact values: Category 1—catastrophic PS: product size2—critical DE: Development environment3—marginal ST: staff size4—negligible

3.5 TIMELINE CHARTS

When creating a software project schedule, the planner begins with a set of task. If automated tools are used, the work breakdown is input as a task network or task outline. Effort, duration, and start

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date are then input for each task. In addition, tasks may be assigned to specific individuals. A timeline chart, also called a Gantt chart, is generated. A timeline chart can be developed for the entire project.

Timeline depicts a part of a software project schedule that emphasizes. All project tasks are listed in the left-hand column. The horizontal bars indicate the duration of each task. When multiple bars occur at the same time on the calendar, task concurrency is implied. The diamonds indicate milestones. Once the information necessary for the generation of a timeline chart has been input, the majority of software project scheduling tools produce project tables—a tabular listing of all project tasks, their planned and actual start- and end-dates, and a variety of related information.

Fig.3.5 Timeline chart

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4. DESIGN ENGINEERING

The design of a system is essentially a blueprint or a plan for a solution for the system. A design methodology is a systematic approach to creating a design approach, a system is viewed as a transformation function, transforming the inputs to the desired outputs.The design process for software systems often has two levels. At the first level the focus is on deciding which modules are needed for the system, the specifications of these modules, and how the modules should be interconnected. This is what is called the system design or top-level design. In the second level, the internal design of the modules, or how the specifications of the module can be satisfied, is decided. This design level is often called design to contain a more detailed description of the processing logic and data structures so that the design is sufficiently complete for coding. 4.1 Architectural Design

For a function-oriented design, the design can be represented graphically by structure charts. The structure of a program is made up of the modules of that program together with the interconnections between modules. The structure chart of a program is a graphic representation of its structure. In a structure chart a module is represented by a box with the module name written in the box.During design, Structured Design Methodology aims to control and influence the structure of the final program. The aim is to design a system so that programs implementing the design would have a hierarchical structure, with functionally cohesive modules and as few interconnection between modules as possible.The overall strategy is to identify the input and output streams and the primary transformations that have to be performed to produce the output. High level modules are then created to perform these major activities ,which are later refined. There are four major steps in this strategy:

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4.1.1. Restate the problem as a Data Flow Diagram No extra inputs or outputs are required to be represented in data flow diagram so DFD remains same as previous.

Fig. 4.1.1 Data flow diagram for Online Voting.

4.1.2 Identify the Most Abstract Input (MAI) and Most Abstract Output(MAO) Data Elements The most abstract input (MAI) data elements are those data elements in the data flow diagram that are farthest removed from the physical inputs but can still be considered inputs to the system. The most abstract input data elements often have little resemblance to the actual physical data.Most abstract output data elements (MAO) by starting from the outputs in the data flow diagram and travelling toward the inputs. These are the data elements that are most removed from the actual outputs but can still be considered outgoing. The MAO data elements may also be considered the logical output data items, and the transforms in the data flow diagram after these data items are basically to convert the logical output into a form in which the system is required to produce the output.

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Figure 4.1.2 DFD with Most Abstract Data Elements

4.1.3 First-level factoring We first specify a main module, whose purpose is to invoke the subordinates. The main module is therefore a coordinate module. For each of the most abstract input data items, an immediate subordinate module to the main module is specified. Each of these modules is an input module, whose purpose is to deliver to the main module the most abstract data item for which it is created. Similarly, for each most abstract data item, a subordinate module that is an output module that accepts data from the main module is specified. Each of the arrows connecting these input and output subordinate modules is labelled with the respective abstract data item flowing in the proper direction. Finally, for each central transform, a module subordinate to the main one is specified. These modules will be transform modules, whose purpose is to accept data from the main module, and then return the appropriate data back to the main module. The data items coming to a transform module from the main module are on the incoming arcs of the corresponding transform in the data flow diagram.

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Fig.4.1.3 DFD for first level factoring

4.1.4 Factoring of input, output and transform branches The first-level factoring results in a very high level structure, where each subordinate module has a lot of processing to do. To simplify these modules, they must be factored into subordinate modules that will distribute the work of a module. Each of the input, output and transformation modules must be considered for factoring. A subordinate input module is created for each input data stream coming into this new central transform, and a subordinate transform module is created for the new central transform. The new input modules now created can then be factored again, untill the physical inputs are reached. The factoring of the output modules is symmetrical to the factoring of the input modules.The goal is to determine sub transforms that will together compose the overall transform and then repeat the process for the newly found transforms, until we reach the atomic modules.

Fig.4.1.4(a) Factoring of Input module

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Fig.4.1.4(b) Factoring of Transform Module

Fig.4.1.4(c) Factoring of Output Module

4.2 Data Design

Data Design translates the data objects defined in the analysis model into data structure that reside within the software. The attributes that describe the object, the relationship between data objects and their use within the program all influence the choice of data structures. At a higher level of abstraction, data design may lead to the definition of the architecture for a database or a data warehouse.

FILE 4.2(a) STUDENT DETAILS

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ATTRIBUTE DATA TYPE LENGTH

NAMEFirst NameSecond NameLast Name

CharCharChar

202020

FATHER’S NAMEFirst NameSecond NameLast Name

CharCharChar

202020

ADDRESS Char 50

SEX Char 1

CONTACT NUMBER Int 12

PASSWORD Char 10

AGE Int 2

COURSE Char 20

USERNAME Char 20

ROLL NUMBER Int 10

ENROLLMENT NUMER Int 10

FILE 4.2(b) ADMINISTRATION

ATTRIBUTE DATA TYPE LENGTH

USERNAME Char 20

PASSWORD Char 20

FILE 4.2(c) LOGIN RELATED DETAILS

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ATTRIBUTE DATA TYPE LENGTH

STUDENTFirst NameSecond NameLast Name

CharCharChar

202020

USERNAME Char 20

PASSWORD Char 10

ROLL NUMBER Int 10

4.3 Component-level Design Component-level design establishes the algorithm detail required to manipulate data structures, effect communication between software components via their interfaces, and implement the processing algorithms allocated to each component. Component-level design, also called procedural design, occurs after data, architectural, and interface designs have been established. The intent is to translate the design model into operational software. But the level of abstraction of the existing design model is relatively high, and the abstraction level of the operational program is low.

PSEUDOCODE:

OVS homepage_Load(){DBconnection.Open Button Login.enable = true Button Logout.enable = true}

Button Login_click(){ Flag =false Username =InputBox(“Enter Your Name”)Password =InputBox(“Enter Your Password”)DBStudent_Details.MoveFirstDo while DBStudent_Details.EOF=false{ ifDBStudent_Details.Feilds(“Username”)<>UsernameAnd DBStudent_Details.Feilds(“Password”)<>Password then DbStudent_Details.MoveNextElse

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flag =true EXIT doEnd if}Loop

if flag =falsethen MsgBox(“Username or Password is not correct”)End ifif flag =true then MsgBox(“Login as voter successful”)Voting Process()End if}Voting Process_Load(){ count_president1= 0count_president2=0count_president3=0count_Vice_president1=0count_Vice_president2=0 “Please select one candidate from each category”{“President Candidate:-” if Radiobutton.1=true then { President =1

count_president1++ } else if Radiobutton.2=true then President=2

count_president2++ } else if Radiobutton.3=true then { President=3

count_president3++ }End if

“Vice President Candidates:-” if Radiobutton.1=true then { Vice president =1

count_Vice_president1++} else if Radiobutton.2=true then

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{ Vice president =2

count_Vice_president2++}End ifButton Save_click(){DBVoting_Details.Feilds(“President”) =PresidentDBVoting_Details.Feilds(“Vice President”) =Vice President}MsgBox(“Voted Successfully”)}}Button Logout_click(){ unload OVShomepage End}

Voting Result Load(){If(count_president1> count_president2 && count_president1> count_president3){

MsgBox(“Selected President is ”, president1)}Else if(count_president2> count_president1 && count_president2> count_president3){

MsgBox(“Selected President is ”, president2)}Else {

MsgBox(“Selected President is ”, president3) }End if

If(count_Vice_president1> count_Vice_president2){

MsgBox(“Selected Vice President is ”, Vice president 1)}Else {

MsgBox(“Selected Vice President is ”, Vice president2 )}End if

5. TESTING

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Testing is the process of running a system with the intention of finding errors. Testing enhances the integrity of a system by detecting deviations in design and errors in the system. Testing aims at detecting error-prone areas. This helps in the prevention of errors in a system. Testing also adds value to the product by conforming to the user requirements.

The main purpose of testing is to detect errors and errorprone areas in a system. Testing must be thorough and well-planned. A partially tested system is as bad as an untested system. And the price of an untested and under-tested system is high.

The implementation is the final and important phase. It involves user-training, system testing in order to ensure successful running of the proposed system. The user tests the system and changes are made according to their needs. The testing involves the testing of the developed system using various kinds of data. While testing, errors are noted and correctness is the mode.

5.1 FLOWGRAPH

Figure 5.1 Flowgraph

5.2 CYCLOMATIC COMPLEXITY

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Cyclomatic complexity is a software metric that provides a quantitative measure of the logical complexity of a program. In figure, the cyclomatic complexity can be computed by using the algorithm.

1. The number of regions correspond to the cyclomatic complexity The flow graph has three regions.

2. Cyclomatic complexity , V(G), for a flow graph, G is defined as V(G)=E-N+2 (where E= no. of edges, N= nodes) V(G)=13 edges – 12 nodes + 2 V(G)= 3

3. Cyclomatic complexity, V(G), for a flow graph G, is also defined as V(G)=P+1= 2+1= 3

Independent Programs PathsAn independent path is any path through the program that introduces atleast new set of processing statements or a new condition. When stated in terms of a graph, an independent bpath must move along atleast one edge that has not traversed before the path is defined.A set of independent paths flow graph illustrated in figure is :path 1: 1-2-4-1path 2: 1-2-3-5-6-7-8-10-12path 3: 1-2-3-5-6-7-8-9-11-12

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REFERENCES

● Software Engineering- A practitioner's Approach by Roger S. Pressman: 6th edition McGraw Hill, 2005

● An Integrated Approach to Software Engineering by Pankaj Jalote: 3rd edition Springer, 2005