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CBSE class 11 commerce Informatics Practices fast track revision notes

CBSE class 11 commerce Informatics Practices fast track revision notes

CBSE class 11 commerce Informatics Practices fast track revision notes:- we will provide complete details CBSE class 11 commerce Informatics Practices fast track revision notes in this article.

CBSE class 11 commerce Informatics Practices fast track revision notes

CBSE class 11 commerce Informatics Practices fast track revision notes

Object Oriented Programming (OOP) means any kind of programming that uses a programming language with some object oriented constructs or programming in an environment where some object oriented principles are followed. At its heart, though, object oriented programming is a mindset which respects programming as a problem-solving dilemma on a grand scale which requires careful application of abstractions and subdividing problems into manageable pieces. Compared with procedural programming, a superficial examination of code written in both styles would reveal that object oriented code tends to be broken down into vast numbers of small pieces, with the hope that each piece will be trivially verifiable. OOP was one step towards the holy grail of software-re-usability, although no new term has gained widespread acceptance, which is why “OOP” is used to mean almost any modern programming distinct from systems programming, assembly programming, functional programming, or database programming. Modern programming would be better categorized as “multi-paradigm” programming, and that term is sometimes used. This book is primarily aimed at modern, multi-paradigm programming, which has classic object oriented programming as its immediate predecessor and strongest influence.

Historically, “OOP” has been one of the most influential developments in computer programming, gaining widespread use in the mid 1980s. Originally heralded for its facility for managing complexity in ever-growing software systems, OOP quickly developed its own set of difficulties. Fortunately, the ever evolving programming landscape gave us “interface” programming, design patterns, generic programming, and other improvements paving the way for more contemporary Multi-Paradigm programming. While some people will debate endlessly about whether or not a certain language implements “Pure” OOP—and bless or denounce a language accordingly—this book is not intended as an academic treatise on object oriented programming or its theory.

Instead, we aim for something more pragmatic: we start with basic OO theory and then delve into a handful of real-world languages to examine how they support OO programming. Since we obviously cannot teach each language, the point is to illustrate the trade-offs inherent in different approaches to OOP.

CBSE class 11 commerce Informatics Practices fast track revision notes

We will divide up OOP into two phases— classic and modern. While this distinction is somewhat arbitrary, we believe it is instructive to consider OOP as it was practiced in the 1980s and early 1990s to demonstrate the motivation for more current practices.

What is Classic OOP?

Object oriented programming can be traced back to a language called Simula, and in particular Simula 67, which was popular during the 1960s. It was Simula that first instituted “classes” and “objects,” leading to the term “object oriented” programming. By the early 1990s, enough experience had been gained with large OOP projects to discover some limitations. Languages such as Self, ideas like interface programming (also known as component or component-oriented programming), and methodologies such as generic programming were being developed in response to these difficulties. Although often derided by OOP purists, it was the standardization of C++ in 1998 —including generic programming facilities — that really ushered in the modern era of OOP, which we also refer to as Multi-Paradigm programming. This is largely due to the popularity of C++ and the genius of the Standard Template Library (STL) demonstrating the utility of the new methodology to such a large audience.

Classic or Pure OOP

By 1980, Xerox had made Smalltalk available to outsiders, appropriately named Smalltalk-80. Unlike other early programming languages, Smalltalk was a complete environment rather than just a language, a characteristic it had in common with Lisp at the time. While Lisp machines were foreshadowing IDEs to come, Smalltalk was pioneering the GUI, ultimately influencing the development of the Macintosh computer. Meanwhile, while Xerox was developing Smalltalk during the 70s, the C language was becoming popular thanks to UNIX being largely written in C. Therefore, it was C —an otherwise unlikely candidate —that Bjarne Stroustrup fused with ideas from Simula to create “C with Classes” which was renamed to C++ in 1983. In 1985, unsatisfied with Smalltalk, C++, and various object systems being tacked onto Lisp dialects, Bertrand Meyer created Eiffel. Even though much more recent, Java essentially cloned vintage C++, and so we consider Smalltalk, vintage C++, Eiffel, and Java to be Classic OOP. The object systems tacked onto Lisp (eventually standardized as CLOS in 1994) produced a very different methodology. While we don’t consider CLOS to be Classic OOP, it did influence modern OOP.

Modern OOP and Multi Paradigm Programming

Classic OOP developed a tendency to over-rely on a technique called “inheritance,” and eventually programmers realized that they were using inheritance for many things that are conceptually distinct. Modern OOP basically incorporates these concepts, sometimes as language level features, sometimes through programmer practice. The goal largely being looser coupling, easier maintenance and reuse. Historically, David Ungar and Randall Smith completed their first working Self compiler in 1987, and by 1990 Sun Microsystems had picked up the project. While Self did not survive to really become a modern OOP language, it was a second generation OOP language. Then, in the early 1990s, Alexander Stepanov and Meng Lee pioneered generic programming and wrote early drafts of C++’s STL. This began a (still ongoing) trend of incorporating functional programming ideas into more traditional OOP environments, in a kind of reverse CLOS. Additionally, the early 1990s saw the development of CORBA and Microsoft’s COM, which was a natural extension of the ideas that had led to the original Windows API. This interface or component programming was a natural extension of encapsulation —a basic tenet of OOP, as we will see. All of these developments were aimed at further managing or reducing complexity. Since this was the original goal of OOP and these techniques are used in conjunction with classic OOP, we find it appropriate to consider them in a treatment on “OOP”.

Contemporary object oriented programming, therefore, tends to be rather distinct from classic object oriented programming. Particularly, getting used to which abstractions are the most useful for which problem types is more challenging now that there are more to choose from! In a now classic book, Gamma et. al. introduced Design Patterns which helped to synthesize a variety of OOP techniques as applied to very common problems.

Future of OOP

The future contains more standardization of functional programming techniques in OOP environments, particularly lambda expressions and closures, and more robust meta-programming constructs. Applying design patterns automatically through generic or meta programming techniques is an interesting area.

CBSE class 11 commerce Informatics Practices fast track revision notes:-Simple Objects vs Behavioral Entities

There are two fundamentally different types of objects, created and designed with different purposes in mind, using different techniques. We label these two types “Simple Objects” and “Behavioral Entities,” although these labels are our own. Simple objects tend to represent values, like colors, coordinates, vectors, strings, etc, while behavioral entities tend to represent system components like services, message queues, engines, application logic, etc.

Simple objects, if they own anything, are just wrapping what they own (like a system level handle). Usually, however, simple objects are untied to anything else, have no complicated startup or shutdown, and have little overhead. Simple objects tend to demand high performance, guaranteed correctness, discourage incorrect usage, are put in collections, searched, passed around, and generally manipulated by the rest of the program. Writing good simple objects, combined with good collection libraries provided by your language of choice, can easily reduce the complexity of basic operations by as much as 80%. Simple objects tend to focus on the encapsulation side of OOP rather than fancy message passing, as it’s usually not a helpful abstraction to think of simple objects sending or receiving messages.

CBSE class 11 commerce Informatics Practices fast track revision notes

Behavioral entities tend to maintain their state in various collections of simple objects, like a server keeping a list of logged in users. Behavioral entities tend to focus on behavior (to state the obvious), and configuring or tailoring that behavior in various circumstances. Message passing mechanisms, including polymorphism, tend to be central to the construction of behavioral entities. As a result, you tend to get whole families of similar entities, for example, an FTP server, an ssh server, an HTTP server, etc. that all have common functionality (like accepting connections).

One of the primary forces behind OOP is separating out all of the common elements from these families and writing it once. This has obvious advantages in debugging and maintenance: you only have to fix bugs in common code once. Obviously, this is just abstraction at work but OOP gives you a well understood set of tools to do it with. Some languages features are tailored for one or the other. For example, operator overloading is truly important for simple objects, but mostly irrelevant for behavioral entities.

CBSE class 11 commerce Informatics Practices fast track revision notes:-Encapsulation

Encapsulation is about risk management, reducing your maintenance burden, and limiting your exposure to vulnerabilities —especially those caused by bypassed/forgotten sanity checks or initialization procedures, or various issues that may arise due to the simple fact of the code changing in different ways over time. Technically, encapsulation is hiding internal details behind an opaque barrier so as to force external entities to interact through publicly available access points.

Think about it in the context of an OS kernel, like the Linux kernel. In general, you don’t want a common user level application modifying any internal kernel data structures directly —you want applications to work through the API (Application Programming Interface). Hence encapsulation is the general term we use for giving varied levels of separation between any core system elements and any common application elements. Otherwise, “unencapsulated code” would be bad for a number of obvious reasons:

  • Applications could easily set invalid or nonsensical values, causing the whole system to crash. Forcing the application to use the API ensures that sanity checks get run on all parameters and all data structures maintain a consistent state.
  • Internal data structures could be updated and change (even drastically so) between seemingly minor kernel updates. Sticking to the API insulates application developers from having to rewrite their code all the time.
  • Applications could be used to “snoop” on each other, elevate their privileges, hog system resources, and violate any number of security protocols if they could directly manipulate kernel data structures.
  • Application developers need little or no understanding of the Linux kernel to access kernel data. The random number engine illustrates this well. It can be accessed through /dev/random instead of wading through kernel structures, and you still get the same data.

There are more, surely you can think of some. You may be thinking, “This is supposed to be about object oriented programming. I don’t want to be a kernel developer!” Yes, we know, but the software kernel is the perfect example for discussing encapsulation, even though the kernel possesses no object oriented code itself. Encapsulation does not strictly apply to OOP, but it is used most within it. All the kernel’s internal data —its message queues, its process lists, its filehandles, etc. —are all encapsulated inside the kernel, and cannot be seen outside the kernel. To work with the kernel, you must use its public interface, the API. For all the same reasons, writing your code in this way pertains the same benefits, even for writing a small app like a text editor or a mail client.

Since the entire purpose of encapsulation is to hide details and restrict access, it makes us consider exactly how access is restricted. It also makes us consider what exactly is a detail that needs to be protected, and what exactly should be exposed to the outside world. Figuring out what to expose, and especially at what granularity, is something of an art and we’ll talk about it more in the section on interfaces. We’ll move on to access restrictions, which come in two basic kinds: compile time and run time.

CBSE class 11 commerce Informatics Practices fast track revision notes

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CBSE class 11 commerce Informatics Practices fast track revision notes

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CBSE class 11 commerce Informatics Practices fast track revision notes

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