B.sc.it Paper Solutions

2019-12-30T23:38:00.003+05:30

The Object Oriented Programming language is one of the powerful and newest model.The “object” in an Object Oriented Programming language discusses to a instance or specific type, of the class. Each and every object has a structure related to other objects in the class, but it can be allocated individual features. An object can also call as method or functions, particular to that object. The Individual characters are may be defined as objects, according to the object which are allows them to have different skill, appearances, and abilities. The Object oriented programming makes it easier to the programmers to design and organize software programs. The important features which are help to design the object-oriented programming and design is given below:

Development over the designed programming paradigm.
Importance on data rather than algorithms.
Procedural abstraction is perfected by data abstraction.
Data and associated processes are unified, grouping objects with common attributes, operations, and semantics.

Characteristics of OOPs

There are twelve characteristics which are given below:

Encapsulation
Data Abstraction
Inheritance
Polymorphism
Extensibility
Persistence
Delegation
Generality
Object Concurrency
Event Handling
Multiple Inheritance
Message Passing

Encapsulation:- It is capturing data and keeping it safely and securely from outside interfaces.
Data Abstraction:- To manage the complexity the role of abstraction is mandatory. To decompose the complex systems into the smaller components the abstraction were used by software developers, however, it has the ability to represent data at very conceptual level without any details.
Inheritance:- This is the process by which a class is derived from a base class with all features of the base class and some of its own. "It will increase the code re-usability".#note: To overcome the short length of this answer please describe the INHERITANCE'S TYPES.
Polymorphism:- The polymorphism means one name, many forms, which is the ability to exist in various forms. For example, an operator can be overloaded so as to add two integer number and two floats.

THAT WAS ENOUGH TO FILL 6 PAGES IN EXAM SHEET. YOU WILL GET 12 OUT OF 15 MARKS EASILY............

Python Data Types

2019-12-11T15:10:00.000+05:30

Python Data Types

Data types are the classification or categorization of data items. It represents the kind of value that tells what operations can be performed on a particular data. Since everything is an object in Python programming, data types are actually classes and variables are instance (object) of these classes.

Following are the standard or built-in data type of python:

Numbers
Sets
Mapping
Sequences
Boolean

Numbers Types in Python

In any OOP language, there are many different data types. In Python, number data types are used to store numeric values. There are four different numerical types in Python:

int : this one is pretty standard -- plain integers are just positive or negative whole numbers.
float (floating point real values): floats represent real numbers, but are written with decimal points (or scientific notation) to divide the whole number into fractional parts.
complex (complex numbers): represented by the formula a + bJ, where a and b are floats, and J is the square root of -1 (the result of which is an imaginary number). Complex numbers are used sparingly in Python.

Sets in Python

In Python, Set is an unordered collection of data type that is iterable, mutable and has no duplicate elements. The order of elements in a set is undefined though it may consist of various elements. The major advantage of using a set, as opposed to a list, is that it has a highly optimized method for checking whether a specific element is contained in the set.

Creating a set
Sets can be created by using the built-in set() function with a sequence by placing the sequence inside curly braces, separated by ‘comma’. A set contains only unique elements but at the time of set creation, multiple duplicate values can also be passed. The order of elements in a set is undefined and is unchangeable. Type of elements in a set need not be the same, various mixed-up data type values can also be passed to the set.

Mapping Types in Python

Dictionary In Python is an unordered collection of data values, used to store data values like a map, which unlike other Data Types that hold only single value as an element, Dictionary holds key:value pair. Key-value is provided in the dictionary to make it more optimized. Each key-value pair in a Dictionary is separated by a colon :, whereas each key is separated by a ‘comma’.

Creating a dictionary In Python, a Dictionary can be created by placing a sequence of elements within curly {} braces, separated by ‘comma’. Dictionary holds a pair of values, one being the Key and the other corresponding pair element being its Key:value. Values in a dictionary can be of any datatype and can be duplicated, whereas keys can’t be repeated and must be immutable.

Dictionary can also be created by the built-in function dict(). An empty dictionary can be created by just placing to curly braces{}.

Note – Dictionary keys are case sensitive, same name but different cases of Key will be treated distinctly.

Sequences Types in Python

Strings Python strings are the instances of class ‘str‘. The string is a sequence of Unicode characters. Python strings are immutable. We can define a string using single quotes (‘) or double quotes(“).String is the most popular data type in Python. There are various operations supported for string objects – length, format, split, join, slicing etc.
Tuple in Python is an ordered sequence of items. Tuple is immutable i.e. once defined we can’t change its values.We can define a tuple using parentheses where items are separated using comma. A tuple can contain any number of elements and the elements can be of any type.
List is almost same as Tuple, except that it’s mutable. The order of the elements is maintained.List is defined using brackets and the elements are separated using comma.

Boolean Types in Python

BooleanData type with one of the two built-in values, True or False. Boolean objects that are equal to True are truthy (true), and those equal to False are falsy (false). But non-Boolean objects can be evaluated in Boolean context as well and determined to be true or false. It is denoted by the class bool.

Note – True and False with capital ‘T’ and ‘F’ are valid Boolean otherwise python will throw an error.

What is a module? Why and How are they used in Python?

2019-12-09T15:07:00.001+05:30

MODULE

In a Python, a module can be defined as a python program file, which contains a python code including python functions. It is essentially a python script file that can contain variables,functions, and classes. The variables can be of any type (array, dictionaries, objects etc.)

Modules can be divided into two sub parts :-

Built in

User-defined

1) User-defined Modules

Create a Module:- To create a module, create a Python file with a `.py` extension.

Call a Module:- Modules created with a .py extension can be used in another Python source file, using the `import` statement.

#callModule.py

import myModule

myModule.myFunction("Python Programming")

2) Built-in Modules

There are several built-in modules in Python, which you can import whenever you like.

Call a built-in Module:- To call a built-in Module and use the function of that module write:

import moduleName #call a module
moduleName.function()#use module function



import math

print("The value of cosine is", math.cos(3))

print("The value of sine is", math.sin(3))

print("The value of tangent is", math.tan(3))

print("The value of pi is", math.pi)

WHY MODULES USED?

There are couple of key that describe the use of modules in python:-

Structured Code

Code is logically organized by being grouped into one Python file which makes development easier and less error-prone.
Code is easier to understand and use.

Reuse ability

Functionality defined in a single module can be easily reused by other parts of the application. This eliminates the need to recreate duplicate code.

HOW THEY ARE USED?

To create a module just save the code you want in a file with the file extension .py:

Example

Save this code in a file named mymodule.py

def greeting(name):
  print("Hello, " + name)

Now we can use the module we just created, by using the import statement:

Example

Import the module named mymodule, and call the greeting function:

import mymodule

mymodule.greeting("Royal")

The Output is:- Hello, Royal

Feature of the Python that Make it Powerful

2019-12-07T15:08:00.001+05:30

Now a days, there are so many types of programming languages, and all have their own specialties. But what feature is make unique that is its features. So let's first take a look at features that makes it powerful.

FEATURES OF PYTHON

Easy
Free and Open Source
Portable
Object-Oriented
High Level
Interpreted
GUI Programming
Large Standard Library
Dynamically Typed
Extensible

Easy:- The python language is easy to code and easy to read. It means, compared to other programming languages like java, c++, it is easier to code in python. Anyone can learn python syntax in just few hours and being a high-level language it is quite like English. Looking at it, you can easily tell what the code is supposed to do.
Free and Open Source:- On the first hand, python is freely available. You can download it from the python website. On the other hand, it is open-source. Means its source code is available to the public. You can download it, change it, use it, and distribute it. This is called FLOSS(Free/Libre and Open Source Software).
Portable:- supposed you have written a python code for your window machine. Now you want to run it on Mac, that you can run easily on the Mac. You don't have to change the code for other operating system. In simple words you can take one code and use it on any operating system, there is no need to write different code for different operating system. This makes python a portable language. However, you must avoid any system-dependent feature in this case.
Object-Oriented:- A programming language that can model the real world is said to be object-oriented. It focuses on objects and combines data and functions. Contrarily, a procedure-oriented language revolves around functions, which are code that can be reused. Python supports both procedure-oriented and object-oriented programming which is one of the key python features. It also supports multiple inheritances, unlike Java. A class is a blueprint for such an object. It is an abstract data type and holds no values.
High Level:- It is a high-level language. This means that as programmers, we don’t need to remember the system architecture. Nor do we need to manage the memory. This makes it more programmer-friendly and is one of the key python features.
Interpreted:- As you know that, in any other languages like java, c++, you must first compile it and then run it. But in Python, there is no need to compile it. By Interpreted, we mean the source code is executed line by line, and not all in once. Because of this, it easier to debug your code.
GUI programming:- A software is not user-friendly until its GUI is made. A user can easily interact with the software with a GUI. Python offers various libraries for making Graphical user interface for your applications. For this, you can use Tkinter, wxPython or JPython. These tool kits allow you for easy and fast development of GUI.
Large Standard Library:- Python downloads with a large library that you can use so you don’t have to write your own code for every single thing. There are libraries for regular expressions, documentation-generation, unit-testing, web browsers, threading, databases, CGI, email, image manipulation, and a lot of other functionality.
Dynamically Typed:- Python is dynamically typed. It means the type for a value is decided at run time, not in advance. This is why we don't need to specify the type of data while declaring it.
Extensible:- When sometime if we need, you can write some of your python code in other languages like C++. This is called Extensible, means that can be extend to other languages.

Operators that Support to Python & Relational and Logical Operators with their Precedence.

2019-12-06T17:28:00.001+05:30

To perform an specific operation the Operators are used. Python has a lot of operators that are either keywords or special characters. These operators are work on with Operands.

TYPES OF OPERATORS

Operators that support to Python can be classified into the following categories:-

Arithmetic Operators:- These are operators for adding, subtracting, multiplication, division, modulus, and exponential operators. All the arithmetic operators are special characters. For example:- (+ : addition), (- : subtract), (* : multiplication) etc.
Comparison Operators:- These operators also called relational operators.These are used to compare two values. The result is always a Boolean value - True or False. For example:-

(= = : return true if both the value are equal)

(>= : return true if the left value is greater or equal to the right value).

Bit wise Operators:- These operators also called binary operators and work on integers only. The value of the operand converted into binary and then perform the operation on every bit. For example:- (& : bit wise AND operator), (^ : bit wise XOR operator).
Logical Operator:- Logical operator work with Boolean operands and return a Boolean value. AND, OR, NOT are the logical operators.
Assignment Operators:- Assignment operator (=) is used to assign the left operand value to the right operand.
There are some compound assignment operators to perform some arithmetic operation between the two operands and then assign the value to the left operand.
- = : simple assignment operator
- += : adds the two operands and then assign the value to the right operand
- -= : subtracts the right operand from the left and then assign the value to the left operand.
Membership Operators:- These operators are used to checking the presence of a value in a sequence. There are two types:- IN or NOT IN. These operators are generally used in if-else condition.
Identity Operators:- These python's operators are used to check if two variables point to the same memory location or not. There are two types:- NOT or IS NOT.

Relational and Logical Operators with their Precedence.

Relational Operators in Python

They are also known as comparison operators because they compare the values on both sides of the operator and conclude on the relation between the values. After comparison, it returns the Boolean value, i.e., either true or false. The following table contains different types of comparison operators and their descriptions, along with respective examples.

Operator	Operator Name	Description	Example
==	Equal to	If values of two operands are equal, then it returns true.	I = 20, J = 20 (I == J) is True
!=	Not Equal to	If values of two operands are not equal, then it returns true.	I = 20, J = 20 (I == J) is False
<	Less than	If the value of the left operand is less than the value of the right operand, then it returns true.	I = 40, J = 20 (I < J) is False
>	Greater than	If the value of the left operand is greater than the value of the right operand, then it returns true.	I= 40, J = 20 (I > J) is True
<=	Less than or equal to	If the value of the left operand is less than or equal to the value of the right operand, then it returns true.	I = 40, J = 20 (I <= J) is False
>=	Greater than or equal to	If the value of the left operand is greater than or equal to the value of the right operand, then it returns true.	I = 40, J = 20 (I >= J) is True
<>	Not equal to (similar to !=)	If values of two operands are not equal, then the condition becomes true.	I=40, J = 20 (I <> J) is True.

Logical Operators in Python

Logical operators are mainly used for conditional statements. There are three types of logical operators, namely, AND, OR, and NOT. The following table contains all logical operators with their descriptions, as well as their respective examples.

Operator	Operator Name	Description	Example
and	Logical AND	When both sides’ conditions are true, the result is true; otherwise false.	2<1 and 2<3 False
or	Logical OR	When at least one condition is true, then result is true; otherwise false.	2<1 or 2<3 True
not	Logical NOT	Reverse the condition	Not (5>4) False

Operator Precedence in Python

Sometimes an expression contains multiple operators. In that case, operator precedence is used to determine the order of execution.

We can create a group of expression using parenthesis. The expression in the parenthesis is evaluated first before they can take part in further calculations.
Some operators have the same level of precedence. In this case, the expression is evaluated from the left to right.

Below lists the Relational and Logical operators precedence in the decreasing order.

==, !=, >, <, >=, <= (Relational(Comparison) Operators)

not, and, or (Logical Operators)

Quality Assurance

2019-12-04T12:35:00.002+05:30

SOFTWARE QUALITY ASSURANCE (SQA)

It is a set of activities for ensuring quality in software engineering processes that ultimately results, or at least gives confidence, in the quality of software products. Quality assurance steps should be taken in each phase to ensure that there are no errors in final product.

The system life cycle considered various stages of development and each stage has a major goal that is the quality assurance. Quality assurance specialists go through system testing before they grant certification.

There are following quality factors which assure the quality of the system.

Correctness:- The extent to which a program meets system specifications and user objectives.
Reliability:- the degree to which the system perform its intended function over a time.
Error Tolerance:- The capacity of error avoidance, error detection and correction.
Usability:- The effort required to learn and operate a system.
Test ability:- The effort required to test a program to ensure its correct performance.
Portability:- The easy way to take a program from one hardware device to another.
Accuracy:- The amount of correctness in input, computation and output.
Expand ability:- The how much easy to add and expand the existing database.

Quality Assurance Goals

Requirement specification

Design specification

Testing and Implementation

Maintenance and support

Level of Quality Assurance

Quality has been defined as a characteristic or an attribute of an entity.Perfect quality is costly and virtually impossible to achieve.There are three level of quality assurance these are:-

Testing:- The common view of testing is to eliminate program errors. A successful testing is that in which we find all errors.
Validation:- System validation checks the quality in both simulated and live environment.
Certification:- The third level of the quality assurance that program software package is correct and confirms to standards. Certificate is given when system passes the testing.

SAD Information Gathering Tools in SDLC

2019-12-03T13:56:00.002+05:30

No two projects are ever the same. This means that the analyst must decide on the information-gathering tool and how it must be used. Although there are no standard rules for specifying their use, an important rule is that information must be acquired accurately, methodically, under the right conditions, and with minimum interruption to user personnel. There are various information-gathering tools. Each tool has a special function depending on the information needed.

SOME DATA COLLECTION METHODS

Interviews
Questionnaires and Surveys
Direct Observation
Focus Groups
Searching Documents and Records

Interviews:- They can be conducted in person or over the telephone. A typical interviews can be done formally (structured), semi-structured, or informally. To conduct an in depth interview, the questions should be focused, clear, and encourage open-ended responses. Interviews are mainly qualitative in nature. There are two major sections of these interviews:

-Personal Interviews: The researcher asks the extra audience questions to get minute details out. This will help get better data for processing.

-Telephonic Interviews: Whenever it is not possible to meet a member of the audience directly, the researcher can call and collect data through a conversation on the phone. This helps collect first-hand data.

Questionnaires and Surveys:- This involves the use of forms which are completed and returned by respondents. It is a fairly inexpensive method that is useful where literacy rates are high and respondents are cooperative. The results are generally easier to compare and analyse.These days, you do not have to share just paper forms as you can if you have it. As long as you have determined that your prospective respondents have access to the internet and would be able to understand the questions without any help from you, this is a good way to collect data is an affordable tool that offers you so many features to aid your data collection process.
Direct Observation:- When you directly observe your subject for a particular period this allows you study the dynamics of a situation and behaviors.The results can produce qualitative (e.g., narrative data) and quantitative data. (e.g., frequency counts, mean length of interactions, and instructional time)
Focus Groups:- This is a facilitated group interview with individuals that have something in common. You are essentially trying to prove if some of the hypotheses you have drawn are indeed true.At the end of this, you should have been able to gather information about combined perspectives and opinions.
Searching Documents and Records:- This consists of examining existing data in the form of databases, meeting minutes, reports, attendance logs, financial records, newsletters, etc. This can be an inexpensive way to gather information but may be an incomplete data source.

Feasibility Study in SDLC

2019-12-02T13:14:00.000+05:30

Feasibility study is the study which involves the analysis of the problem domain and collection of all vital information in relation to the product to select the best system that meets requirements.In simpler terms, it is an analysis of how successful a project can be carried out.Project managers use feasibility studies to discern the pros and cons of undertaking a project before the invest a lot of time and money into it. Feasibility studies also can provide a company's management with crucial information that could prevent the company from entering blindly into risky businesses.

To determine if the product is technically and financially feasible to develop, is the main air of the feasibility study activity.

The main objective of the feasibility are mentioned below:-

To analyze if the software meets organizational requirements.
To determine if the software can be implemented using the current technology and within the specified budget and schedule.
To find whether the software can be integrated with other existing software.

TOPIC UNDER FEASIBILITY STUDY

The various topic include feasibility study are:-

Technical Feasibility
Operational Feasibility
Economic Feasibility
Legal Feasibility
Scheduling Feasibility

Technical Feasibility:- In technical feasibility the following issues are taken into consideration:-

- Whether the required technology is available or not?

- Whether the required resources are available?

- Manpower programmers, testers & debuggers.

- Software & Hardware.

The assessment focuses on the technical resources available to the organization. It helps organizations determine whether the technical resources meet capacity and whether the technical team is capable of converting the idea into working system. Technical feasibility also involves evaluation of the hardware, software and other technical requirements of the proposed system.

Operational Feasibility:- This assessment involves undertaking a study to analyze and determine whether-and how well-the organization's needs can be met by completing the project. Operational feasibility studies also examine how a project plan satisfies the requirements identified in the requirements analysis phase of system development.
Economic Feasibility:- For any system is the excepted benefits equal or exceed the excepted costs, the system can be judge to be economically feasible. Economic analysis is used for evaluating the effectiveness of the proposed system. In economic feasibility the most important is cost benefit analysis. As the name suggest it is an analysis of the cost to be incurred in the system and benefits derivable out of the system.
Legal Feasibility:- This assessment investigates whether any aspect of the proposed project conflicts with legal requirements like zoning law, data protection acts or social media laws. Let's say an organization wants to construct a new office building in a specific location. A feasibility study might reveal the organization's ideal location isn't zoned for that type of business. That organization has just saved considerable time and effort by learning that their project was not feasible right from the beginning.
Scheduling Feasibility:- This assessment is the most important for project success; after all, a project will fail if not completed on time. In scheduling feasibility, an organization estimates how much time the project will take to complete.

When these areas have all been examined, the feasibility analysis helps identify any constraints the proposed project may face, including:-

- Internal Project Constraints: Technical, Technology, Budget, Resource, etc.

- Internal Corporate Constraints: Financial, Marketing, Export, etc.

- External Constraints: Logistics, Environment, Laws, Regulations, etc.

Types of Maintenance Procedures SDLC

2019-12-01T17:35:00.002+05:30

Maintenance in general , can be defined as efforts taken to keep the condition and performance of a machine always link the conditions and performance of the machine when it is still new.

The types of maintenance cannot be equated for each equipment, which depends on the method, cast and critical level. The following types of maintenance methods are commonly used in several industries.

TYPES OF MAINTENANCE

Preventive Maintenance
Predictive Maintenance
Corrective Maintenance
Adoptive Maintenance

Preventive Maintenance:- It is a method for preventing damage to equipment by periodically replacing parts based on the time of use and carrying out minor maintenance and inspection to find out the current state of the equipment/machinery. examples:- cleaning, checking, lubricating etc.
Predictive Maintenance:- Predictive maintenance is a method for doing replacing coding at the back end of software and also predictive maintenance involves making functional enhancement to the system in addition to the activities to increase the system's performance even when the changes have not been suggested by faults.
Corrective Maintenance:- Corrective Maintenance is a method for doing replacing coding at the background of software and also predictive maintenance involves making. It is also deals with the repair of faults or defect found in today system function. A defect can result due to errors in software design, logic and coding.

Design errors occurs when changes made to the software are incorrect, incomplete, wrongly communicated or the change request is misunderstanding.
Logical errors results from invalid tests and conclusions, incorrect implementations of design specifications, faulty logic flow or incomplete test of data. All these errors referred to as residual errors.

4. Adoptive Maintenance:- Adaptive maintenance is the implementation of changes in a part of the system , which has been affected by a change that occurred in some other part of the system. Adaptive maintenance consist of adapting software to changes in the environment such as the hardware or the operating system. The term environment in this context refer to the conditions and influences which at the system . examples:- business rules, work patterns and government policies have a significant impact on the software system.

Types of Testing in SDLC

2019-12-01T15:14:00.001+05:30

Testing is a process of executing a program with the aim of finding error to make our software perform will it should be our error free. If testing is done successfully it will remove all the errors from the software.

PRINCIPLES OF TESTING

All the test should must meet the customer requirement.
To make our software testing should be performed by third party.
Executive testing is not possible. As we need the optional amount of testing based on the risk assessment of the application.
All the test to be conducted should be planned before implementing it.
If follows parts rule(80/20 rules) which states that 80% of errors comes from 20% of programs components.

TYPES OF TESTING

Unit Testing
Integration Testing
Regression Testing
Alpha Testing
Beta Testing
System Testing
Stress Testing

Unit Testing:- Unit Testing is the testing of an individual unit or group of related units. It falls under the class of white box testing. It is often done by the unit he/she has implemented is producing expected output against given output.
Integration Testing:- Integration testing is testing in which a group components are combined to produce output also, the interaction between software and hardware is tested in integration testing if software and hardware have any relation.
Regression Testing:- Regression testing after modification of a system components, or a group of related units to ensure that the modification is working correctly and is not damaging or imposing other values to produce unexpected results.
Alpha Testing:- This testing is also known as acceptance testing.This is the testing we do just before handover the project or software to the client.This is the testing the QA department perform most of the time to check all the things OK when we are delivering it to the customer or not.
Beta Testing:- Beta testing is the testing which is done by end users, a team outside development, or publicly releasing full version of the product. which is known as beta version. The aim of beta testing is to cover unexpected errors.
System Testing:- System testing is the testing to ensure that by putting the software in different environment (e.g. operating system) it still works. System testing is done with full system implementation and environment.
Stress Testing:- Stress testing is the testing to evalute how system behave under unfavorable condition. Testing is conducted of beyond limits of the specifications. It falls under the class of black box testing.

System Development Life cycle SDLC

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SDLC

As the name implies,the system development life cycle is a multi step procedure of software.which is structured in a methodical way. In other words, it can be defined as a project management model that define the stages involved in bringing a project from beginning to completion. The term system involves abet on system development life cycle or SDLC, is often pitched later talking just roughly the software move on the process, but many people have only an unclear idea about what the process actually involves.

let's suppose you are about the board on a software or a web development project that you want to take your business to the next level, you may be surprised to be learn that the project builds actually occurs. The process of software development services goes through a series of steps that almost every software development company follows.

Steps in SDLC

It is well known that programming software or a application for a developer can be slightly stressful at times, especially when it comes to coding different parts of a big project. Thus having a perfect system which allows you to take the development process step by step without felling overwhelmed is essential to producing a high quality piece of software.

Usually, 7 stages of the system development life cycle (SDLC) are:

Planning
Requirement
System design
Development
Testing
Implementation or Coding
Operator and Maintenance

Planning:- First, you can have to plan of course, you are going to start a project on your own and planning is the process of deciding what you new information system should look like? and then identify the resources needed to develop it.
Requirement:- The analysis is very important to proceed further to the next step. In this step, you will analyse the performance of the software at various stages and make notes on further requirements.
Design:- This stage is relatively simple in comparison to the other stages of the SDLC. Here, you will see a blueprint of the software that you the application, network database, user interface and the system interface.
Development:- Now the actual task of developing the software starts with this step. Here, you start building your information system. Hardware is purchased and installed and software is coded and then loaded on a testing platform.
Testing:- Your quality analyst staff will conduct the testing process. They make sure that your information system can work properly with your existing system.
Implementation:- Once, the software is developed, the stages of implementation comes. After excessively testing your program to make sure that there's nothing wrong with it, your;s ready to implement it. Here you need to implement the design into source code through coding. Therefore, it is software time taking. In fact, this is the longest phase of the software development life cycle.
Maintenance:- The final step is to go through a maintenance process where the software will be maintained and upgraded from time to get use to the changes. It totally depends on the feedback you get from the customers. It also includes handling the renaming errors and resolves any issues, which may exist in the system even after the testing phase.

B.sc.it Paper Solutions

Characteristics of OOPs

THAT WAS ENOUGH TO FILL 6 PAGES IN EXAM SHEET. YOU WILL GET 12 OUT OF 15 MARKS EASILY............

Python Data Types

Python Data Types

Numbers Types in Python

Sets in Python

Mapping Types in Python

Sequences Types in Python

What is a module? Why and How are they used in Python?

MODULE

In a Python, a module can be defined as a python program file, which contains a python code including python functions. It is essentially a python script file that can contain variables,functions, and classes. The variables can be of any type (array, dictionaries, objects etc.)

Modules can be divided into two sub parts :-

Built in User-defined

1) User-defined Modules

Create a Module:- To create a module, create a Python file with a .py extension.

Call a Module:- Modules created with a .py extension can be used in another Python source file, using the import statement.

2) Built-in Modules

Call a built-in Module:- To call a built-in Module and use the function of that module write:

WHY MODULES USED?

HOW THEY ARE USED?

Example

Example

Feature of the Python that Make it Powerful

FEATURES OF PYTHON

Operators that Support to Python & Relational and Logical Operators with their Precedence.

TYPES OF OPERATORS

Relational and Logical Operators with their Precedence.

Operator Precedence in Python

Quality Assurance

SOFTWARE QUALITY ASSURANCE (SQA)

Quality Assurance Goals

Requirement specification Design specification Testing and Implementation Maintenance and support

Level of Quality Assurance

SAD Information Gathering Tools in SDLC

SOME DATA COLLECTION METHODS

Feasibility Study in SDLC

The main objective of the feasibility are mentioned below:-

TOPIC UNDER FEASIBILITY STUDY

Types of Maintenance Procedures SDLC

TYPES OF MAINTENANCE

Types of Testing in SDLC

PRINCIPLES OF TESTING

TYPES OF TESTING

System Development Life cycle SDLC

Built in

User-defined

Create a Module:- To create a module, create a Python file with a `.py` extension.

Call a Module:- Modules created with a .py extension can be used in another Python source file, using the `import` statement.

Requirement specification

Design specification

Testing and Implementation

Maintenance and support