level task. SDLC is used as a first step[5] for Project planning. There are numerous models exist for software development in which prototype model is one.
IJCST Vol. 2, Issue 1, March 2011
ISSN : 2229-4333(Print) | ISSN : 0976-8491(Online)
Improving the Efficiency of Prototype Model using Pareto Principle 1 1,2,3
Anupriya Jain, 2Sachin Sharma, 3Seema Sharma
Deptt. Of Computer Applications, Manav Rachna International Univ., Faridabad, Haryana, India
Abstract The various activities that are undertaken when developing software are commonly modeled as a software development life cycle. It begins with identification of requirements of software and ends with retirement of software .The SDLC is the progression of high level task that are used to develop software. It is the first step in project planning process. There are no. of different models of software development life cycle like, waterfall model, prototyping, Spiral, Iterative, and so on. The prototype model imitates effort to increase the flexibility of the development process by permitting the customer to interact with a working model of the product. The major problem to be faced that the management some time consider the prototype as final model. This will lead to a problem as prototype is not complete and no one can measure the reliability, complexity and efficiency. Through the Pareto principal, we can minimize this problem up to certain extent. A principle named after Vilfredo Pareto that specifies an unequal relationship between inputs and outputs. The principle states that for many phenomena, 20 % of invested input is responsible for 80% of the results obtained. Put another way, 80% of the consequences stem from 20% of the causes. It is also referred to as the “Pareto Rule” of the “80/20 Rule”. Keywords Development, Pareto, Requirement Analysis, Implementation, Prototyping. I. Introduction To develop software, we need SDLC which is progression of high level task. SDLC is used as a first step[5] for Project planning. There are numerous models exist for software development in which prototype model is one. Prototype model[4] is a SDLC model in which software prototype created for user feedback and refining the prototype for further elaboration. The main focus of this model is on (i) the basic requirements (ii) Version of working prototype (iii) Verification and Refining of working prototype (iv) Changing and elaboration requirements The problem that occurs in prototype model is that it constitutes high level of risk if the management considers the prototype as a final product[2]. Secondly, strong management is also requiring since the developers are not confident in software algorithm because the user changed the requirement time to time. This will lead to a waste of time[ and delay in a final product and high level of complexity. But if we apply 80/20 rule, we can reduce or minimize this problem up to some extent. Pareto principle established in 1897 by an Italian Vilfredo Pareto in England when he observed that 20% of the people of Italy owned 80% of the wealth. This concept of disproportion holds in many areas. This law states that 20% of something is always responsible for 80% of the results. We can apply this rule in almost anything in the management.
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There are many situations in real life where this principle[7] follows: a) 80% of result produces through 20% of the time expanded. b) 20% of the streets handle 80% of the traffic. c) 20% of the paper has 80% of the news. d) 80% of your phone calls go to 20% of the names in your list e) 20% of the people cause 80% of the problems and so on. The important thing is that we have to consider or notice such disproportions and act possibly on such observations. II. Discussions and Results: A. Problem Statement: In order to discuss that how Pareto principle is useful in prototype model, we will first take a problem for Student Management System of M.Sc(IT) program of a University. The program consists of 4 semesters with 4 theory papers and 2 lab papers till third semester. In the 4th Semester, student has to submit the dissertation on a subject of their own interest. There are two compulsory papers and two optional papers and are offered from Ist to IIIrd Semester to each student. The student can take any two subjects out of choices available for optional papers. The requirements to develop a system is that - Manage information about subject offered in various semester. - Number of students enrolled in various semester. - Papers that are taken by various students in different semester. - Result Analysis and marks obtained by the student in different semester. B. Pareto’s Steps: Pareto principle is used in many applications in Quality Control and Six Sigma [7]. There are following steps for Pareto analysis which are used in order to identify the most important causes. 1. We generate a table that lists the causes and their occurrence as percentage. 2. Sort the above table in decreasing order of importance of the cause. 3. Calculate the cumulative percentage of the frequency for the above table. 4. Plot a curve by taking causes on x-axis and cumulative frequency on y-axis and on the same graph, we again draw a Bar Graph taking percent frequency on y-axis and x-axis remains same. . 5. Draw a line at 80% on y-axis parallel to x-axis. Drop the line at the point of intersection with the curve on x-axis. This point on the x-axis separates the important causes on the left and less important causes on the right.
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IJCST Vol. 2, Issue 1, March 2011
ISSN : 2229-4333(Print) | ISSN : 0976-8491(Online)
C. Analysis The detailed implementation of the steps with the problem is as follows : Table 1: List of Causes with Frequencies a. Generate a table Causes Frequency (%) Cumulative (in Decreasing order) Frequency 1. Course List 16.6 16.6 2. Semester wise 33.3 49.9 List of students 6. Result Analysis 16.6 66.5 3. Program details
16.6
83.1
5. Pass Criteria 7. Aggregate Result
8.3 8.3
91.4 99.7
4. List of lectives semester wise
16.6
116.3
Table 2: Sorted table with the Cumulative Frequency b. Sort the above table Causes Occurrence Percentage 1. Course List 2 16.6 2. Semester wise List of 4 33.3 students 3. Program Details 2 16.6 4.List of Electives semester wise
2
16.6
5. Pass Criteria 6. Result Analysis
1 2
8.3 16.6
7.Aggregate Result
1
8.3
C. Plot a graph and curve
40
5
20
0
0
References [1] Pressman, R., S., 1998, "Software Process Improvement". In: Software Engineering – A Practitioner’s Approach, Fourth Edition, Software Project Management. pp.78. McGraw- Hill Companies Publication, Inc. USA [2] Kuhl, 2002, "Project Lifecycle Model: How they differ and when to use them". [3] Futrell, R., T., Shafer, D., F., Shafer L. I., 2004, “Waterfall Model Activities”. In: ‘QUALITY SOFTWARE PROJECT MANAGEMENT, 3rd Edition’. pp. 269-271. (Pearson Education Publication, India). [4] Pressman, R., S., 1998, “The Linear Sequential Model”. In: ‘SOFTWARE ENGINEERING – A PRACTITIONER’S APPROACH, FOURTH EDITION’. pp. 30- (McGraw- Hill Companies Publication, Inc. USA). [5] Parida, P., 2006, “Essence of Waterfall Model”. [6] Aggarwal K.K., Singh Yogesh, 2007, “Software Engineering”, pp. 23-26 [7] Pareto Analysis Step by Step, By Duncan Haughey, PMP
cumulative frequency
60
10
Prototype may be different from the final system so feedback based on the prototype may not apply to the final system. - Prototypes are poor specifications because they are incomplete. - A prototype can not express many non-functional requirements. By applying Pareto Prototype 80% of the requirement can be traced to 20% of all possible cause, so isolate 20% (the vital few). We have applied the Pareto Principle on the above mentioned case study and determine the various important causes to be filtered for developing a prototype. Now on applying the above mentioned points of Pareto’s principle, the developer can concentrate only on the requirement of the system which saves vital time and system becomes reliable, efficient. Hence we get the prototype which is made through the 20% of the most important causes that are reliable and can be treated as a final prototype which will closely resemble to the final product and less error prone.
Aggregate Result List of Electives semester wise
80
15
Pass Criteria
100
20
Program Details
120
25
Result Analysis
140
30
Semester wise List of students
35
Course List
frequency
Pareto Analysis for Student database management system
-
causes
Fig. 1: Graph representing Frequency of the causes The above graph shows that the important causes (Course List, Semester wise list of students, Result Analysis and Program Details) exist on the left side of the dotted line and least important causes are the right side of curve. Keeping these requirements mentioned above for developing a prototype model, the model will be more close to the problem and will provide accurate user feedback. III. Conclusions Prototyping model [3] is based on developing an initial model of the problem and based on the user feedback, the software is finally developed but this approach has certain drawbacks [1]: w w w. i j c s t. c o m
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IJCST Vol. 2, Issue 1, March 2011
ISSN : 2229-4333(Print) | ISSN : 0976-8491(Online)
Anupriya Jain is currently working as Asstt Professor in Computer Science, Manav Rachna International University, Faridabad, India. Her qualifications are M.Tech (IT), M.Phil (Computer) and DOEACC B Level. She has 9+ years experience of teaching undergraduate and post graduate students. She has published 2 research papers in International conferences and participated in many National/ International Conferences to her credit. Her research interests are in the areas of Software Engg and Computer Organization. She has also written a book on “Computer Architecture” for MCA.
Sachin Sharma is currently working as Asstt Professor in Computer Science, Manav Rachna International University, Faridabad, India. He is working towards his Ph.D in Operations Research at MDU, Rohtak, India. His qualifications are M.Tech(IT), M.Phil (Computer), MCA and M.Sc(Operations Research). He has 12+ years experience of teaching undergraduate and post graduate students. He has published 2 research papers in International conferences and participated in many National/ International Conferences. His research interests are in the areas of Software Engg, Data Structures and Operations Research. He has also written books on “Computer Architecture” for MCA and “Programming in C” for GJU, Hisar.
Seema K. Sharma is currently working as Asstt Professor in Computer Science, Manav Rachna International University, Faridabad, India. Her qualifications are M.Phil(Computer) and MCA. She has 5+ years experience of teaching undergraduate and post graduate students She has published 2 research papers in International conferences and participated in many National/ International Conferences. Her research interests are in the areas of Software Engg, Data Structures and Java. She has also written books on “Computer Architecture” and Computer Fundamentals & IT Tools” for MCA.
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