Soft Loc
Soft Loc
Software cost estimation
Abstract
Viewing Software cost is the process of predicting the effort required to develop a software system. This paper provides a general overview of software cost method appreciation including recent advances the field. As a number of models rely on a software size estimate as input, we first provide an overview of common metrics size. Then we highlight the model cost estimation proposed and successfully used. Models can be classified in 2 main categories: non-algorithmic and algorithmic. Each has its own strengths and weaknesses. An important factor in choosing a cost model of opinion is the accuracy of its estimates. Unfortunately, despite large body of experience in the model estimation, the accuracy of the model is not satisfactory. The paper includes comments on the performance of the model estimation and description some newer
approach to cost opinion.
Keywords: project estimation, effort estimation, cost sa model.
1. Introduction
In recent years, the software has become the most expensive part of computer system projects. The bulk of the cost of software development efforts for the people, and most costs theory techniques focus on this aspect and give estimates in terms of person-months.
Accurate software cost estimates is critical to both developers and customers. They can be used for developing requests for proposals, contract negotiations, scheduling, monitoring and control. Underestimating the costs can result in management agree that the proposed system then exceed their budgets, with underdeveloped function and poor quality, and failure to complete on time. Overestimating can result in too many resources committed to the project, or, during the contract bidding, result in winning The contract, which can lead to unemployment
.
Accurate cost estimation is important because:
- Be can help to sort and prioritize projects in development with respect to a general business plan.
- It can be used to determine what resources to make the project and how well resources are used.
- It can be used to assess the impact of changes and support replanning.
- Projects can be easier to manage and control when resources are better matched to real needs.
- Customers depending on the actual cost growth to be in line with estimated costs.
- Viewing Software cost involves determining one or more of the following estimates:
- effort (usually in person-months)
- project duration (calendar time)
- value (in dollars)
Most cost values model attempts to produce an effort estimate, which can then be
convert the project duration and cost. Although efforts and costs are closely related, they are not necessarily related by a simple change-function form. Efforts are often measured in the month of year of programmers, analysts and project manager. Effort estimate can be converted to a dollar cost figure by calculating an average pay per unit of time of staff involved, and then multiplying it by the estimated effort required.
Professionals struggled with three main issues:
- Which software cost model estimation to use?
- Which software size measurement used – lines of code (LOC), function points (fp), or feature point?
- What is a good estimate?
The broad practiced costs of the opinion is expert judgment. For many years, the project
managers have relied on the experience and the prevailing industry practices as a basis to develop the cost estimate. However, basing estimates on expert judgment are problems:
- Approach is not and repeatable means of deriving an estimate are not clear.
- It is difficult to find highly experienced estimators for each new project.
- The relationship between costs and system size is not long. Cost Plus tends
exponentially in size. The expert system of discretion is appropriate only when the size of current projects and past projects are similar.
- Budget manipulations by management aimed prevent spread of work experience and data from previous projects is dubious.
The past three decades, much of the volume software cost estimation models are developed. They range from empirical models such as models Cocomo Boehm sa analytical model. From the observations a model uses data from previous projects to evaluate the current project and derives the basic formulas from the analysis of particular database available. An analytical model, on the other hand, uses formulas based on global assumptions, such as the rate of the developer to resolve the problem and the number of problems available.
Most cost models are based on the size measure, such as LOC and fp, obtained from size
opinion. The accuracy of the size of the verdict directly impact the accuracy of the cost opinion. Although the average size measurements self drawbacks, an organization can make good use of any one, as long as a consistent method of counting is used.
A good software cost estimate should have the following characteristics:
- It was conceived and supported by project manager and development team.
- It is accepted all customers occur.
- It is based on a clear model of software cost a fabulous basis.
- It is based on a database of relevant project experience (similar process, such as
technology, such as environment, such as human and similar requirements).
- It is defined in sufficient detail so that its key risk areas are understood and the possibility of success is really assessed.
Software costs regard history is a major problem in software development.
There are many reasons for poverty are identified:
- Lack of a historical database of cost measurement
- Software related to development of many interrelated factors that affect the development effort and productivity, and his relationships are not well understood
- Lack of trained estimators and estimators with the necessary expertise
- Little punishment is often associated with a poor estimate
2. Process of opinion
Cost estimation is an important part of the process of planning. For example, the top-down planning approach, the cost estimate is used to take the project plan:
- The project manager develops a description of the overall functionality, size, process, environment, people, and quality required for the project.
- A Macro-level estimates of total effort and schedule was developed using software cost theory model.
- The project manager partitions the analyst estimate in a top-level work breakdown structure. He also partitions the schedule the major milestone dates and sets Staffing profile, which together form a project plan.
The actual costs in the process of opinion involves seven steps
- Establish cost-estimating purposes
- Create a project plan for data needed and resources
- Pin down software requirements
- Work out more details about the software system as feasible
- Use some independent cost estimation procedures to impose their unified strength
- Compare various estimates and repeat process of opinion
- After the project is started, monitor the actual costs and development, and comment the results of the project management
No matter which model estimation is selected, users must pay attention to the following to get the best results:
- coverage of the estimate (some models of efforts to develop the entire life-cycle, while others are not included in efforts for the needs stage)
- calibration and treatment models
- sensitivity of estimates to different parameters of the model
- deviation of estimates with respect the actual costs
3. Software sizing
The size software is the most important factors affecting the software cost. This section
describes the size five software metrics used in medicine. The lines of code and function point is the most popular measure between five metrics.
Line Code: This is the number of lines delivered source code of the software, excluding comments and blank lines and is commonly known as LOC. Even LOC is both programming language, it is the most widely used software size metric. Most models related to measuring the value of software. However, the exact LOC can only get after the project is completed. Estimating the code size of a program before it actually contained almost as hard as estimating the value of program.
A typical method for estimating the code size is to use experts' judging with a
technique called with no respect. It involves experts' judging of three possible code-size: SL, the lowest possible size; SH the highest possible size, and SM, the most likely size. The estimate of the code-size S is computed as:
S = S1 + +4 SH SM
6
Irreverent can also be used for individual components to get an estimate of system software by summing the estimates of all components.
Software science: Halstead proposed that the code length and number of metrics. Code length is used to measure the source code of the program and the length is defined as:
N = N1 + N2
N1 which is the total number of Part of the operators, and N2 is the total number of operand parts.
Amount corresponds to the amount of required storage space and is defined as:
V = N log (n1 + n2)
where n1 is the number of unique operator, and n2 is the number of unique operands that appear in a program.
Function points: This is a measurement based functions of the program and was first introduced by Albrecht. The total number of points that function depends on the number of unique (in terms of format or processing logic) forms the following five classes:
- User-input types of data or control of the user-input types of
- User-output type of output data types the user leaves the system
- Inquiry type: interactive inputs requiring a response
- Internal file types: files (logical groups of information) used and distributed within the system
- External file types: files that are passed or shared between system and other systems. Each type of individual is assigned one of three levels of complexity (1 = simple, 2 = medium, 3 = complex) and given a weighting value different from 3 (for simple input) to 15 (for complex internal files).
The unadjusted function-point counts (UFC) is given as
5 3
UFC =? NW
i = 1 j = 1 ij ij
where N ij and W ij are respectively the number and weight of these types of classes I J complex.
Sample, If the raw function-point counts of a project is simple 2 inputs (W ij = 3), 2
complex outputs (W ij = 7) and 1 complex internal files (W ij = 15). After UFC = 3 + 2 * 2 * 7 +1 * 15 = 35.
This is the first function-point number is either used directly for the costs or opinion is further modified by the things that the value depends on the overall complexity of the project. It will take account level distributed processing, the amount again, the performance requirements, etc. The last function-point count is the product of UFC and project complexity factors. The advantage of function-point measurement is that it can be available based on system specifications required in the early stages of the software longer.
The UFC is also used for code-size of appreciation with the following linear formula:
LOC = a + b * UFC
The parameter a, b can be obtained using linear and returning completed before the project data. The final Function Point Counting Practices Manual is maintained by the IFPUG (International Function Point Users Group).
Extension of the function point: Feature point extends the functions points to include the algorithm as a new class. Algorithm is defined as a set of rules that which should be fully expressed in resolving a significant computational problem. For example, a square root usually can consider as an algorithm. Each algorithm used is given a weight ranging from 1 (elementary) to 10 (sophisticated algorithm) and the feature point is the weight sum of the algorithm and the function points. Measurement is especially useful for systems with some input / output and high algorithmic complexity, such as mathematical software, discrete simulation, and military applications.
Another extension of function points is full function point (FFP) for measuring real-time
application, by also taking into consideration the control aspects of such applications. FFP introduces two new control over data function types and four new control transactional function types.
Object points: While the feature point and FFP extend the function point, the point of measuring object size from a different dimension. Measurement is based on the number and complexity of the following items: screens, reports and 3GL components. Each of these items are counted and given a weight ranging from 1 (simple screen) to 10 (3GL part) and the object point is the weight sum of all things. This is a relatively new measurement and that it is very popular. But because it is easy to use in the early cycle of development and also measured the size of software that is reasonably good, measurement is used in models of primary importance like Cocomo II for cost estimation.
4. Opinion Cost
There are two main types of procedures that cost estimation: non-algorithmic and algorithmic.
Algorithmic models widely vary in mathematical sophistication. Some are based on simple arithmetic formula such as the use of summary statistics of mean and standard Deviations. Others are based on return models and usage equation. To improve the accuracy of algorithmic models, there is a need to change or calibrate the model to local circumstances. The model can not be use off-the-shelf. Even with calibration the accuracy can be quite mixed.
We first provide an overview non-algorithmic techniques.
4.1 Non-algorithmic Methods
Uniformity costs: The method requires one or more completed projects like the new project and obtained the verdict by of reasoning by analogy using the actual costs of past projects. Opinion by analogy can make either the entire project level or subsystem level. The total level of the project is the advantage that all cost components of the system is considered as the subsystem level is the advantage of providing a more detailed analysis of the similarities and differences between new projects and completed projects. The strength of this method is that estimates are based on actual project experience. However, it is not clear to what extend the previous project was the true representative of limitation, environmental and functions performed by new system.
Expert decision: The scheme involves consulting one or more experts. The experts provide the estimates using their own methods and experiences. Expert-consensus mechanism such as Delphi method or no respect will be used to resolve the inconsistencies in the estimates. The Delphi technique works as follows:
1) The coordinator of presents each expert with details and estimates form a record.
2) Each expert fills in the form individually (without talking to others) and is allowed to ask the coordinator of questions.
3) The coordinator prepares a summary of all the estimates from experts (including the mean or median) in a form requesting another repetition experts' estimates and the rationale for the estimates.
4) Repeat steps 2) -3) as many rounds as appropriate.
The modified Delphi method proposed by Boehm and Fahquhar seems more effective: Before the verdict, a group meeting involving coordinator and experts organized to discuss the issues opinion. In step 3), the experts are not required to provide any rationale for estimates. Instead, after each round of opinion, coordinator calls a meeting to have experts discussing the points where their estimates widely vary.
Parkinson: The use of Parkinson's principle "work expands to fill the available volume", cost is determined (not estimated) by available resources rather than based on an objective analysis. When the software is delivered to 12 months and 5 persons are available, the efforts are estimated to 60 person-months. Although it sometimes gives good values, this method is not recommended as it can provide very unrealistic estimates. Additionally, this method does not promote good software engineering practice.
Price-to-win: The software cost is estimated that the best price to win the project. The appreciation is based on the customer's budget instead of functions of software. For example, if the a reasonable distinction for a project costs 100 man-months but the customer can only afford 60 man-months it was common estimator is asked to change the opinion to fit 60 months of the year 'efforts to win the project. It is again not a good practice because it is very likely to cause a bad transmission delay or force the development team in overtime work.
Bottom-up: This way, each part of the system the software is separately estimated and the results aggregated to produce an estimate for the overall system. The need for this approach is that an initial design should be in place indicating how the system is decomposed in different parts.
Top-down: This approach is the opposite of the bottom-up manner. An overall estimate of costs for the system came from the global properties, using either algorithmic or non-algorithmic techniques. The total cost may then diverge among the different parts. Approach is more suitable for cost appreciation in the early stages.
4.2 Algorithmic Systems
The algorithmic methods based on mathematical model to make cost estimates as a function of a number of variables, which are considered to be the primary factor costs. Any algorithmic models are the form:
Effort = f (x 1, x 2, …, xn)
where (x 1, x 2, …, xn) denote the cost factor. The existing algorithmic techniques differ in two aspects: the choice of cost factors, and the form of function f. We first discuss the things that used to cost models, and identify the model according to the form and function the models are analytical or empirical.
4.2.1 Cost factors
Besides the size of software, with many other cost factors. The most comprehensive set of cost factors is proposed and used by Boehm et al models Cocomo II. The cost of the things that could be divided into four types:
Product factors: demand excellence; product complexity; database size used; necessary
reusability; documentation match to life-cycle needs;
Computer factors: execution time constraint; main storage constraint; computer turnaround limitations; platform volatility;
Personnel factors: ANALYST ability; application experience; programming skills;
platform experience; language and tool experience; continuity of staff;
Project factors: multisite development; use of software tools; necessary development of schedule.
The above factors are not always independent, and most of them are difficult to quantify. In many models, some factors appear in unified form and some are just ignored. Also, some factors that discrete value, resulting in a function of opinion on a piece-wise form.
4.2.2 Linear models
The length of the model is the form:
n
Effort = A0 + A reduction
i = 1 i I
where coefficients a 1, …, a n are chosen to best fit the complete project data. The work of Nelson belongs to this type models. We agree with Boehm's comment that too many nonlinear interactions in software development for a linear model to work well ".
4.2.3 Multiplicative model
Multiplicative models has the form:
n XI
Effort = A0? An
i = 1 I
Again the coefficients a 1, …, a n are chosen to best fit the complete project data. Walston-Felix used this type of model in each x i getting only three possible values: -1, 0, +1. Doty model also belongs to class every x I taking only two possible values: 0, +1. The two models will seem too strict on the amount of cost factors.
4.2.4 Power function model
Power function of the model is the general form:
Effort = a 'S b
where S is the code-size, and, b is (usually simple) function of other cost factors. Class that contains the two most popular algorithmic models in use, as follows:
Cocomo (constructive Cost Model) model
The family of models proposed by Boehm. This model is widely accepted usage. In COCOMOs, the code-size S is given a thousand LOC (KLOC) and efforts are on man-month.
A) Basic Cocomo. This model uses three sets of (a, b) depending on the complexity of software only:
(1) for simple, well understood applications, a = 2.4, b = 1.05;
(2) for more complex system, a = 3.0, b = 1.15;
(3) for embedded system, a = 3.6, b = 1.20.
The basic Cocomo model is simple and easy to use. Like many cost factors are not
considered, it can only be used as a rough estimates.
B) Intermediate and Detailed Cocomo Cocomo. In intermediate Cocomo, a small estimation effort was obtained using the power function in three sets (a, b), with a coefficient being slightly different from that of the main Cocomo:
(1) for simple, well understood by the application, a = 3.2, b = 1.05
(2) for the more complex system, a = 3.0, b = 1.15
(3) for embedded system, a = 2,8, b = 1.20
Then, fifteen things cost value ranging 0.7-1.66 (see Table 1) was determined [5]. The overall impact factor M is already the product of all individual factors, and the estimate is obtained by multiplying M on nominal estimates.
Table 1: The cost factors and their weight sa Cocomo II
Cost factors
Description
Rating
Very low
low
nominal
High
Very high
Products
Hope
required software reliability
0.75
0.88
1.00
1.15
1.40
DATA
database size
—
0.94
1.00
1.08
1.16
CPLX
product complexity
0.75
0.85
1.00
1.15
1.30
Computer
TIME
Execution time constraint
—
—
1.00
1.11
1.30
STOR
main storage constraint
—
—
1.00
1.06
1.21
VIRT
virtual machine volatility
—
0.87
1.00
1.15
1.30
TURN
computer turnaround time
—
0.87
1.00
1.07
1.15
Personnel
ACAP
ANALYST capacity
1.46
1.19
1.00
0.86
0.71
AEXP
application experience
1.29
1.13
1.00
0.91
0.82
PCAP
programmer ability
1.42
1.17
1.00
0.86
0.70
VEXP
virtual machine experience
1.21
1.10
1.00
0.90
—
LEXP
language experience
1.14
1.07
1.00
0.95
—
Project
MODP
modern training programs
1.24
1.10
1.00
0.91
0.82
Tool
software tools
1.24
1.10
1.00
0.91
0.83
SCED
development of schedule
1.23
1.08
1.00
1.04
1.10
While the same basic and intermediate rate COCOMOs software system costs
level, the detailed work Cocomo each sub-system separately and have an obvious
advantage for large systems containing non-identical subsystems.
C) Cocomo II. Perhaps the most significant difference from the early Cocomo the model is the symbol b changes according to the following cost factors: precedentedness, development flexibility, architecture or risk resolution, team cohesion, and process maturity. Other differences include the newly added factors of cost and solidifying model for software architecture and reducing risk.
Putnam's SLIM model and
Putnam derives his model based on Norden / Rayleigh distribution staff and its search study completed many projects. The central part of Putnam's model is called the software equation as follows:
S = E '(effort) 1 / 3 td 4 / 3
t where d is the software delivery time; E is the environment factor that reflects the ability of development, can be derived from historical data using software
equation. The size S is the LOC and effort is in person-years. Another important relationfound by Putnam is
Effort = D 0 '3 TD
where D 0 is a parameter called staff build-up which ranges from 8 (all new software with many interfaces) to 27 (rebuilt software). Combining the above equations with equation software, we obtain the power function form:
Effort = (D04 / 7 x E-9 / 7) X S9 / 7 and
td = (D0-1 / 7 x E-3 / 7) x S3 / 7
Putnam's model is also widely used in practice and SLIM is a software tool based on the model for cost estimation and staff scheduling.
4.2.5 Model calibration using linear recurrence
The direct application of the above models do not take local circumstances into consideration.
- However, one can fix the thing that costs using local data and the length return method. We describe this calibration models using the general power function model: effort = an 'S b.
Take logarithm of both sides and let Y =- log (effort), A =- log (a) and X =- log in (S). The formula is transformed into a line equation:
Y = A + b 'X
Applying standards least square method to a set of past project data (Y i, X i: i = 1, …, k), obtained We are required parameters b and A (and therefore a) for power function.
4.2.6 Discrete models
Discrete models have tabular form, usually related to the effort, duration, difficulty and other cost factors. It kind of model contains models Aron, Wolverton model and Boeing models. The models get some popular the first day cost of opinion, that they are easy to use.
4.2.7 Other models
Many other existing models and the following is used quite successfully in practice.
Price of-S is owned software cost model theory developed and maintained by RCA, New Jersey. Starting from an estimate of project size and type of poverty, The model computes project cost and schedule.
SoftCost relevant size, effort and duration to address risk using a form of Rayleigh distribution probability. It contains heuristics to guide the estimators in dealing with new technologies and complex relationship between the parameters involved.
The algorithmic models can be grouped as shown in Table 2.
Table 2. Classification of algorithmic models
Algorithmic Models
Linear
Multiplicative
Power Function
Discrete
Other
From empirical
Nelson
Walston-Felix herd in et
COCOMOS
Aron Boeing Wolverton
Price a-S
Analytical
Putnam
Soft Cost
Table 3 compares the strengths and weaknesses of different methods. From the comparison, we can conclude that
- No one on the way is the best for all projects.
- Parkinson and Price-to-win methods are not suitable for organizations which aims to win the additional business.
- Using a combination of techniques can provide the best opinion. For example, add top-down opinion on the expert judgments and similarity methods can provide a superior result.
Table 3. Summary of strengths and weaknesses of various procedures
Procedures
Power
Weakness
Non-algorithmic
Expert Punishment
Expert with relevant experience can provide a good sense;
Rely on 'expert';
May bias;
Suffer from incomplete recall
Analogy
Based on actual project data and past experience
Similar projects may not exist;
Historical data may be inaccurate
Parkinson price-to-win
Often the contract
Poor / weak training;
Can have a huge OVERRUNS
Top-down
System level focus;
Faster and easier than bottom-up system;
Required minimal project detail
Provide little detail for justifying
estimates;
More accurate than other methods
Bottom-up
Based on detailed analysis;
Support project tracking better than the other way, as it estimates address low level of activities
May see the level of the system of things cost;
Require more estimation effort
compared to the Top-down;
Difficult to perform estimates early in lifecycle
Algorithmic
Purpose, repeatable results;
Get a better understanding of the notion of system
Subjective inputs;
Calibrated in the previous project and may not reflect the current environment;
Algorithm can be company specific and not suitable for software
development in general
4.3 Measuring model performance
Various researchers have used different measurements error. The most popular error measure is Mean Absolute relative error (Mare):
n
Mare = A (| (estimatesi – actuali) / actuali |) / n
i = 1
where the estimates I The effort is estimated from the model, the actual me is the actual effort, and n is the number of projects.
To establish if the model is biased, the Mean relative error (MRE) can be used:
MRE = = A (| (estimatesi – Actuali) / actuali |) / N
A large positive MRE would suggest models generally overestimates effort, while a large negative value indicates in reverse.
The following criteria will be used for evaluation of cost models of opinion:
1) Definition – Has the model clearly defined the costs it is estimating, and the cost is not included?
2) Integrity – Are the estimates close to actual costs expended on the project?
3) objectivity – the model avoid allocating most of the difference software costs poorly calibrated subjective things (such as complexity)? Is it difficult to adjust the model to get any results the user want?
4) Constructiveness – Can a user tell why the model gives its estimates? Does help the user understand the software work done?
5) Detail – The model easily accommodate the notion of a software system consisting of a number of subsystems and units? Does it give accurate phase and activity breakdowns?
6) Stability – not small differences in inputs produce small differences in estimates cost output?
7) Range – the model to cover the types of software project costs estimates users need?
Ease of Use – Are the model inputs and options easy to understand and specify?
9) Prospectiveness – Does the model avoid the use of information is also not known until the project is complete?
10) parsimony – The model avoid the use a highly redundant reasons, or reasons that make no appreciable contribution to the result?
5. Performance models verdict
Many studies have attempted to evaluate the model costs opinion. Unfortunately, the results are not encouraging, as many of them found to be very accurate. Kemerer performed an empirical validation of four algorithmic models (SLIM, Cocomo, Estimacs, and FPA). No recalibration of the model is performed on the data project, which is different from that used for model development. Most models showed a strong over estimation bias and large error sense, ranging from a Mare of 57% to 800%.
Vicinanza, Mukhopadhyay Prietula experts and used in estimating the project effort using the Kemerer data without formal algorithmic techniques and found the results outperformed the models original study. However, the Mare range 32-1107%.
Ferens and Gurner evaluated three models (covers, checks, and COSTAR) with 22
projects from Albrecht's database and 14 projects from Kemerer data set. The appreciation of the error is large, with Mare ranging from 46% for check model 105% for the COSTAR model.
Another study also found Cocomo high error rate, averaging 166%. Jeffery and Low investigated the need for model calibration in both the industrial and organizational level. No model calibration, the estimation error is large, with Mare ranging from to 43% to 105%.
Jeffery, Low and Barnes later compared to SPQR/20 FPA model using data from 64 projects from one organization. The model is recalibrated to the local environment to remove biases opinion. Improving estimates will follow with a Mare of 12%, reflecting the benefits of model calibration.
There are also studies on the use of common. By using a program called
Angels that are based sa Minimization of Euclidian distance to n-dimensional space, Shepperd and Schofield found that estimating by analogy outperformed discrimination based on statistics derived algorithm.
Heemstra surveyed 364 organizations and found that only 51 used models to estimate effort and that the model users made no better rate than non-model users. Also, using models of opinion is not better than expert judgments.
A survey software development within the JPL found that only 7% of estimators use
algorithmic model as a basic strategy of opinion.
6. New approaches
Cost estimation remains a complex problem, which continues to attract considerable research attention. Researchers have attempted different techniques. Recently, models based on artificial intelligence techniques are developed. For example, Finnie and Wittig artificial applied neural networks (Ann) and in the case based on other – (CBR) in the sense of effort. Using a set of data from the Australian Software Metrics Association, Ann is able to estimate development effort within 25% of actual effort to over 75% of the project, and by the disturbance of less than 25%. However, results from the CBR is more encouraging. Sa 73% of cases, the estimates are within 50% of actual effort, and for 53% of cases, the estimates are within 25% of the actual na.
In a separate study, Mukhopadhyay, Vicinanza and Prietula found that an expert system based on analogical reasoning outperformed other methods.
Srinivasan and Fisher used in machine learning method based on the full return and neural networks to estimate costs. The study of the procedures were found to be competitive sa SLIM, Cocomo, and function points, compared to the previous study by Kemerer. The main advantage of the system of education is that they are adaptable and nonparametric.
Briand, El Eman, and Bomarius proposed a hybrid cost modeling method, Cobra: Cost
opinion, benchmarking and Risk Analysis. This method is based on expert knowledge and project the amount of data from a small number of projects. Encouraging results are reported in a small data.
About the Author
CURRICULUM VITAE
Objectives: -
Develop the desktop and Distributed Database Applications through the
application tools like :
C/C++, Visual Basic (Database Connectivity With Oracle or SQL Server2000,Ms-Access,Crystal Report)
Java, HTML, DHTML, Visual C++, ASP (Active Server Pages), VbScript, JavaScript.
Personal: – E-Mail: nomaniba@yahoo.com
Name: Muhammad Noman Siddiqui
F/Name: Muhammad Saeed Siddiqui
D.O.B: 13th June 1980
Sex: Male
Marital Status: Married
Nationality: Pakistani
Address: B-6/229 Indus Mehran Society,
Malir Extension Karachi.Pakistan
P.O.Box: 75080
Cell No: 0345-3623475
Experience: -
I have One year Teaching Experience in an Global Computer Institute.
C/C++,Visual Basic,Ms-Office(Ms-Word,Access,Excel)
SQL Server 2000,Crystal Report.
Qualification:-
Academic:-
Graduation:
MS (Network &Telecommunications;)
from Mohammad Ali Jinnah University
BS (Computer Science)
from Orasoft Training Institute
Affiliated With University Of Shah Abdul,Sindh
Intermediate: H.S.C from Govt Dehli Science College
Matric : S.S.C From F.J Grammar School
Strength:-
Handling and Design the Desktop Applications Through Visual Basic With Database Connectivity Like Sql Server-2000,Ms-Access and Oracle.
Handling and Design the Distributed Applications Through ASP and Jsp with the database connectivity like Ms-Access,Sql-Server-2000 and Oracle 8i.
Projects:-
• Library Information System
• Inventory Control System
• Sale/Purchase System (Designed in Visual Basic)
• Fixed Assets Management System(Under Process)
Reference:-
I have listened through my colleague.So consider me as an employee candidate in your concerned department of your organization.
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Drive-Loc VI Reversible Screwdriver Blade Set with Standard Soft Grip Handle, 5 Pieces … |
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Busse Bag Ice Large Soft-loc Sontara W/tie Strings 25/bx 2bx/cs $93.52 Features of the Busse Dupont Sontara Ice Bags: The new and improved ice bags from Busse have been designed to make the caregiver’s job faster and easier while providing the patient with cold, yet dry therapy. These innovative ice bags have been thoroughly researched to meet all of the clinicians and patient’s needs. The absorbent layer between the inner bag and the Sontara® materia… |
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`Rollator 4-Wheel Junior w/PS 6 Casters w/Loop Locks Blue $147.27 Blue Frame * 6 casters with soft-grip tires are ideal for indoor and outdoor use * Tool Free removable padded back rest for comfort * 18 floor to seat height * Manufactured with wrap-around welds providing additional strength and support * Comfortable p… |
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`Rollator 4-Wheel Junior w/PS 6 Casters w/Loop Locks Red $142.40 Red Frame * 6 casters with soft-grip tires are ideal for indoor and outdoor use * Tool Free removable padded back rest for comfort * 18 floor to seat height * Manufactured with wrap-around welds providing additional strength and support * Comfortable pa… |
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Dante’s Disneyland Inferno [RARE] A1 Sexy Graveyard (11:50) A2 Hector And Chino (4:32) A3 Soft Fragile Eggshell Minds (2:43) A4 Flesh Balloons Of Tibet (1:20) A5 Pay The Fiddler (1:53) A6 The Brothers Unconnected (3:06) B1 A Bad Dream (1:23) B2 The Geography Of The Swastika (11:11) B3 Hippie Conglomerate (0:52) B4 Five Minutes (1:08) B5 Persistance Of Vision (1:18) B6 Charles Gocher Sr. (7:16) C… |
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Terrapin SS-100 Soft Shell Notebook Backpack $39.99 … |
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V Tech – Nursery Rhyme Rockin’ Cube $14.99 … |
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Vtech – V.Smile Soft Songs Baby Phone $14.99 Ring! Ring! It’s for baby. The Soft Songs Baby Phone? is the portable solution for little telephone talkers on the go. Baby presses the bright flashing buttons to activate friendly phrases and popular melodies for play time or sleepy time. The take-along phone also features a soft, padded bumper and a baby-safe self-discovery mirror that makes “peek-a-boo” irresistible…. |
Loc Loops/Soft Spike Curls
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NEW Alpine Soft Loc 3 Arrow Quiver APG $48.99 |
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NEW Alpine Soft Loc 3 Arrow Quiver MATHEWS HARDWOODS HD $48.99 |
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NEW Alpine Soft Loc 3 Arrow Quiver MATHEWS LOST CAMO $48.99 |
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NEW Alpine Soft Loc 3 Arrow Quiver MOSSY OAK $48.99 |
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NEW Alpine Soft Loc 3 Arrow Quiver RT HARDWOODS GRN HD $48.99 |
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NEW Alpine Soft Loc 5 Arrow Quiver APG $48.99 |
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NEW Alpine Soft Loc 5 Arrow Quiver BLACK $48.99 |
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NEW Alpine Soft Loc 5 Arrow Quiver HARDWOODS HD MATHEWS $48.99 |
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NEW Alpine Soft Loc 5 Arrow Quiver MATHEWS LOST CAMO $48.99 |
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NEW Alpine Soft Loc 5 Arrow Quiver MOSSY OAK $48.99 |
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NEW Alpine Soft Loc 5 Arrow Quiver MOSSY OAK TREESTAND $48.99 |
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NEW Alpine Soft Loc 5 Arrow Quiver NEXT CAMO $48.99 |
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NEW Alpine Soft Loc 5 Arrow Quiver RT HARDWOODS GRN HD $48.99 |
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NEW Alpine Soft Loc Quiver TREE MOUNT $16.99 |
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NEW Alpine Soft Loc Quiver TREESTAND MOUNT $16.99 |
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Alpine Archery Soft Loc 5 Arrow Quiver $47.99 |
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NEW Alpine Soft Loc 3 Arrow Quiver AP GREEN $46.40 |
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NEW Alpine Soft Loc 3 Arrow Quiver HARDWOODS HD MATHEWS $46.40 |
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NEW Alpine Soft Loc 3 Arrow Quiver MATHEWS LOST CAMO $46.40 |
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NEW Alpine Soft Loc 3 Arrow Quiver MOBU $46.40 |
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NEW Alpine Soft Loc 3 Arrow Quiver NEXT GEN1 NG1 $46.40 |
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NEW Alpine Soft Loc 3 Arrow Quiver RT HWDS GREEN HD $46.40 |
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NEW Alpine Soft Loc 5 Arrow Quiver AP GREEN $46.40 |
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NEW Alpine Soft Loc 5 Arrow Quiver BLACK $46.40 |
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NEW Alpine Soft Loc 5 Arrow Quiver HARDWOODS HD MATHEWS $46.40 |
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NEW Alpine Soft Loc 5 Arrow Quiver MATHEWS LOST CAMO $46.40 |
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NEW Alpine Soft Loc 5 Arrow Quiver MOBU $46.40 |
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NEW Alpine Soft Loc 5 Arrow Quiver MOSSY OAK TREESTAND $46.40 |
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NEW Alpine Soft Loc 5 Arrow Quiver NEXT GEN1 NG1 $46.40 |
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NEW Alpine Soft Loc 5 Arrow Quiver RT HWDS GREEN HD $46.40 |
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ALPINE SOFT LOC MOBU 5 ARROW BOW QUIVER $80 $39.99 |
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ALPINE ARCHERY – SOFT LOC 7 ARROW QVR HRDWD HD $49.99 |
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5 ARROW ALPINE SOFT LOC REALTREE AP HUNTING QUIVER NEW! $48.95 |
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Alpine Soft Loc 5 Arrow Quiver (Black) $54.99 |
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Alpine Soft Loc 5 Arrow Quiver (HD Green) $54.99 |
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Alpine Archery, Soft Loc Quiver, 5 Arrow, Mossy Oak BU $52.50 |
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ALPINE ARCHERY SOFT LOC QUIVER 5-ARROW Color: Realtree $53.92 |
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ALPINE ARCHERY SOFT LOC QUIVER 5-ARROW Color: Mossy Oa $53.92 |
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ALPINE ARCHERY SOFT-LOC 3 ARROW QUIVER $55.00 |
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ALPINE ARCHERY SOFT LOC QUIVER 5-ARROW FOR MATHEWS BOWS $53.92 |
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Alpine Archery Quiver Soft Loc 3Arrow MOSSY OAK BREAKUP $45.88 |
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Alpine Archery Quiver Soft Loc 3 MOSSY OAK TREESTAND $45.88 |
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Alpine Archery Quiver Soft Loc 3MATHEWS HARDWOODS HD $45.88 |
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Alpine Archery Quiver Soft Loc 7 Arrow HARDWOODS GREEN $45.88 |
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Alpine Archery Quiver Soft Loc 7 Arrow NEXT G-1 CAMO $45.88 |
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Alpine Archery Soft Loc Quiver Compact Tree Stand Mount $16.95 |
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ALPINE SOFT LOC 5 ARROW QUIVER MOTS $49.99 |
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ALPINE SOFT LOC 5 ARROW QUIVER HRDWD GRN $49.99 |
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ALPINE ARCHERY – SOFT LOC 5 ARROW QVR MTHWS LOST $49.99 |
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ALPINE ARCHERY – SOFT LOC 5 ARROW QUIVER BRKUP $49.99 |
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ALPINE ARCHERY – SOFT LOC 5 ARROW QUIVER BLACK $47.50 |
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ALPINE ARCHERY – SOFT LOC 5 ARROW QUIVER AP GRN $49.99 |
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ALPINE ARCHERY – SOFT LOC 3ARROW QVR HRDWD GRN $49.99 |
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ALPINE ARCHERY – SOFT LOC 3 ARROW QUIVER NG1 $49.99 |
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ALPINE ARCHERY – SOFT LOC 5 ARROW Quiver Hardwood Green $55.99 |
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ALPINE ARCHERY – SOFT LOC 3 ARROW QUIVER MTHWS LOST $49.99 |
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ALPINE ARCHERY – SOFT LOC 3 ARROW QUIVER B.U. $49.99 |
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ALPINE ARCHERY – SOFT LOC 3 ARROW QUIVER AP GRN $49.99 |
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Alpine Archery Mounting Assembly – 7, 5, 3 Soft Loc $13.75 |
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Alpine Archery Replacement Foam – 5 Arrow Soft Loc $3.95 |