- Introduction
- Electronic Computing
- Boolean Logic
- Number Systems
- Central Processing Unit(CPU)
- Registers, Cache and RAM
- Instruction and Program
- Programming Language
- Data Types
- Statements and Functions
- Data Structures
- Algorithms
- Alan Turing
- Software Engineering
- Integrated Circuits
- Object Oriented Programming
- Operating Systems
- Memory and Storage
- File System
- Cloud Computing
- Machine Learning
- Web Technology
- Networking and Network Protocols
Computer science is the study of computers and computing as well as their theoretical and practical applications. Computer science applies the principles of mathematics, engineering, and logic to a plethora of functions, including algorithm formulation, software and hardware development, and artificial intelligence.
A device that computes, especially a programmable electronic machine that performs high-speed mathematical or logical operations or that assembles, stores, correlates, or otherwise processes information.
Boolean logic is a branch of mathematics that deals with the values of truth and falsehood. It is a system of logic that uses only two values, 0 and 1, to represent false and true, respectively. It is also known as Boolean algebra, named after George Boole, who first described it in 1854.
Operator | Name | Description |
---|---|---|
! | NOT | Negates the value of the operand. |
&& | AND | Returns true if both operands are true. |
|| | OR | Returns true if either operand is true. |
Operator | Name | Description |
---|---|---|
() | Parentheses | Allows you to group together keywords and control the order in which the terms will be searched. |
“” | Quotation marks | Provides results with the exact phrase. |
* | Asterisk | Provides results that contain a variation of the keyword. |
⊕ | XOR | Returns true if the operand are diffrent. |
⊽ | NOR | Returns true if neither operand are true. |
⊼ | NAND | Returns false value only if both values of its two inputs are true. |
Number systems are mathematical systems for expressing numbers. A number system consists of a set of symbols that are used to represent numbers and a set of rules for manipulating those symbols. The symbols used in a number system are called numerals.
Binary is a base-2 number system invented by Gottfried Leibniz that's made up of only two numbers or digits: 0 (zero) and 1 (one). This numbering system is the basis for all binary code, which is used to write digital data such as the computer processor instructions used every day. The 0s and 1s in binary represent OFF or ON, respectively. In a transistor, a "0" represents no flow of electricity, and a "1" represents electricity is allowed to flow. In this way, numbers are represented physically inside the computing device, permitting calculations.
Binary is still the primary language for computers and is used with electronics and computer hardware for the following reasons.
- It is a simple and elegant design.
- Binary's 0 and 1 method is quick to detect an electrical signal's off (false) or on (true) state.
- Having only two states placed far apart in an electrical signal makes it less susceptible to electrical interference.
- The positive and negative poles of magnetic media are quickly translated to binary.
- Binary is the most efficient way to control logic circuits.
A central processing unit (CPU) is an important part of every computer. The CPU sends signals to control the other parts of the computer, almost like how a brain controls a body. The CPU is an electronic machine that works on a list of computer things to do, called instructions. It reads the list of instructions and runs (executes) each one in order. A list of instructions that a CPU can run is a computer program. A CPU can process more than one instruction at a time on sections called Cores. A CPU with four cores may process four programs at once. The CPU itself is made of three main components. They are:
Registers are small amounts of high-speed memory contained within the CPU. Registers are basically a collection of flip-flops (a circuit used to store 1 bit of memory). They are used by the processor to store small amounts of data that are needed during processing. A CPU may have several sets of registers that are called Cores. Register also helps in arithmetic and logic operations.Larger amounts of data may be stored in Cache (pronounced like cash). This is a very fast memory that is located on the same integrated circuit as the registers. It is used for data frequently needed as the program runs. Still larger amounts of data may be stored in RAM. These are integrated circuits not part of the CPU. RAM stands for random-access memory. It is essentially data and instructions that have been moved from disk storage and held until the processor needs it.
A cache -- pronounced CASH -- is hardware or software that is used to store something, usually data, temporarily in a computing environment.
RAM (Random Access Memory) is the hardware in a computing device where the operating system (OS), application programs and data in current use are kept so they can be quickly reached by the device's processor. RAM is the main memory in a computer. It is much faster to read from and write to than other kinds of storage, such as a hard disk drive (HDD), solid-state drive (SSD) or optical drive.
In computer science, an instruction is a single operation of a processor defined by the processor instruction set. And a computer program is a list of instructions that tell a computer what to do. Everything a computer does is done by using a computer program. Programs stored in the memory of a computer ("internal programming") let the computer do one thing after another, even with breaks in between.
A programming language is any set of rules that convert strings, or graphical program elements in the case of visual programming languages, to various kinds of machine code output.[citation needed] Programming languages are one kind of computer language and are used in computer programming to implement algorithms.
Programming languages are mainly of two types :
- High-level language uses a syntax similar to the English language. The source code is converted into machine-understandable machine code using a compiler or an interpreter. Java, Python are some examples of high-level programming languages.
- Low-level programming languages work more closely to the hardware and have more control over it. They directly interact with the hardware. Two common examples of low-level languages are machine language and assembly language.
Some Languages Include:
- Python
- Java
- C++
- C
- C#
A scripting language is a computer language that doesn't have to be compiled. One advantage of Scripting languages is that the code can be quickly edited and can be re-executed. They can be used on the server side of web applications and the client side of web applications.
Some Scripting Languages include:
- Javascript
- PHP
- Python
- Perl
A data type, in programming, is a classification that specifies which type of value a variable has and what type of mathematical, relational or logical operations can be applied to it without causing an error.
Primitive data types are the most basic data types in a programming language. They are the building blocks of more complex data types. Primitive data types are predefined by the programming language and are named by a reserved keyword.
Non-primitive data types are also known as reference data types. They are created by the programmer and are not defined by the programming language. Non-primitive data types are also called composite data types because they are composed of other types.
In computer programming, a statement is a syntactic unit of an imperative programming language that expresses some action to be carried out. A program written in such a language is formed by a sequence of one or more statements. A statement may have internal components (e.g., expressions). There are two main types of statements in any programming language that is necessary to build the logic of a code.
There are two types of conditional statements mainly:
- if-else
- switch case
There are three types of conditional statements mainly:
- for loop
- while loop
- do - while loop (a variation of while loop)
A function is a block of statements that performs a specific task. Functions accept data, process it, and return a result. Functions are written primarily to support the concept of reusability. Once a function is written, it can be called easily, without having to write the same code again and again.
Different functional languages use different syntax to write a function.
Read more about functions here
In computer science, a data structure is a data organization, management, and storage format that enables efficient access and modification. More precisely, a data structure is a collection of data values, the relationships among them, and the functions or operations that can be applied to the data.
Algorithms are the sets of steps necessary to complete computation - they are at the heart of what our devices do. And this isn’t a new concept. Since the development of math itself algorithms have been needed to help us complete tasks more efficiently, but today we’re going to take a look at a couple of modern computing problems like sorting and graph search, and show how we’ve made them more efficient so you can more easily find cheap airfare or map directions to Winterfell... or like a restaurant or something.
The time complexity of an algorithm estimates how much time the algorithm will use for some input. The idea is to represent efficiency as a function whose parameter is the size of the input. By calculating the time complexity, we can find out whether the algorithm is fast enough without implementing it.
Sorting is the process of arranging a list of items in a particular order. For example, if you had a list of names, you might want to sort them alphabetically. Or if you had a list of numbers, you might want to put them in order from smallest to largest. Sorting is a common task, and it’s one that we can do in many different ways.
Searching is algorithm for finding a certain target element inside a container. Searching Algorithms are designed to check for an element or retrieve an element from any data structure where it is stored.
Graph search is the process of searching through a graph to find a particular node. A graph is a data structure that consists of a finite (and possibly mutable) set of vertices or nodes or points, together with a set of unordered pairs of these vertices for an undirected graph or a set of ordered pairs for a directed graph. These pairs are known as edges, arcs, or lines for an undirected graph and as arrows, directed edges, directed arcs, or directed lines for a directed graph. The vertices may be part of the graph structure or may be external entities represented by integer indices or references. Graphs are one of the most useful data structures for many real-world applications. Graphs are used to model pairwise relations between objects. For example, the airline route network is a graph in which the cities are the vertices and the flight routes are the edges. Graphs are also used to represent networks. The Internet can be modelled as a graph in which the computers are the vertices and the links between computers are the edges. Graphs are also used on social networks like LinkedIn and Facebook. Graphs are used to represent many real-world applications: computer networks, circuit design, and aeronautical scheduling to name just a few.
Dynamic programming is both a mathematical optimization method and a computer programming method. The method was developed by Richard Bellman in the 1950s and has found applications in numerous fields, from aerospace engineering to economics. In both contexts, it refers to simplifying a complicated problem by breaking it down into simpler sub-problems in a recursive manner. While some decision problems cannot be taken apart this way, decisions that span several points in time do often break apart recursively. Likewise, in computer science, if a problem can be solved optimally by breaking it into sub-problems and then recursively finding the optimal solutions to the sub-problems, then it is said to have an optimal substructure. Dynamic programming is one way to solve problems with these properties. The process of breaking a complicated problem down into simpler sub-problems is called "divide and conquer".
Greedy algorithms are a simple, intuitive class of algorithms that can be used to find the optimal solution to some optimization problems. They are called greedy because at each step they make the choice that seems best at that moment. This means that greedy algorithms do not guarantee to return the globally optimal solution, but instead make locally optimal choices in the hope of finding a global optimum. Greedy algorithms are used for optimization problems. An optimization problem can be solved using Greedy if the problem has the following property: at every step, we can make a choice that looks best at the moment, and we get the optimal solution to the complete problem.
Backtracking is an algorithmic technique for solving problems recursively by trying to build a solution incrementally, one piece at a time, removing those solutions that fail to satisfy the constraints of the problem at any point in time (by time, here, is referred to the time elapsed till reaching any level of the search tree).
Branch and bound is a general technique for solving combinatorial optimization problems. It is a systematic enumeration technique that reduces the number of candidate solutions by using the problem's structure to eliminate candidate solutions that cannot possibly be optimal.
Time Complexity: It is defined as the number of times a particular instruction set is expected to be executed rather than the total time is taken. Since time is a dependent phenomenon, time complexity may vary on some external factors like processor speed, the compiler used, etc.
Space Complexity: It is the total memory space consumed by the program for its execution.
Both are calculated as the function of input size(n). The time complexity of an algorithm is expressed in big O notation.
The efficiency of an algorithm depends on these two parameters.
Types Of Time Complexity :
a. Best Time Complexity: The input for which algorithm takes less time or minimum time. In the best case calculate the lower bound of an algorithm. Example: The search data is present at the first location of large data in the linear search then the best case occurs. b. Average Time Complexity: We take all random inputs and calculate the computation time for all inputs. And then we divide it by the total number of inputs. c. Worst Time Complexity: Define the input for which algorithm takes a long time or maximum time. In the worst calculate the upper bound of an algorithm. Example: The search data is present at the last location of large data in the linear search then the worst case occurs.
Some time complexities are :
a. O(1): This denotes the constant time. 0(1) usually means that an algorithm will have constant time regardless of the input size. Hash Maps are perfect examples of constant time.
b. O(log n): This denotes logarithmic time. O(log n) means to decrease with each instance for the operations. Binary search trees are the best examples of logarithmic time.
c. O(n): This denotes linear time. O(n) means that the performance is directly proportional to the input size. In simple terms, the number of inputs and the time taken to execute those inputs will be proportional or the same. Linear search in arrays is the best example of linear time complexity.
d. O(n*n): This denotes quadratic time. O(n2) means that the performance is directly proportional to the square of the input taken. In simple, the time taken for execution will take square times the input size. Nested loops are perfect examples of quadratic time complexity.
Algorithm | Time Complexity | Space Complexity | ||
---|---|---|---|---|
Best | Average | Worst | Worst | |
Selection Sort | Ω(n^2) | θ(n^2) | O(n^2) | O(1) |
Bubble Sort | Ω(n) | θ(n^2) | O(n^2) | O(1) |
Insertion Sort | Ω(n) | θ(n^2) | O(n^2) | O(1) |
Heap Sort | Ω(n log(n)) | θ(n log(n)) | O(n log(n)) | O(1) |
Quick Sort | Ω(n log(n)) | θ(n log(n)) | O(n^2) | O(n) |
Merge Sort | Ω(n log(n)) | θ(n log(n)) | O(n log(n)) | O(n) |
Bucket Sort | Ω(n +k) | θ(n +k) | O(n^2) | O(n) |
Radix Sort | Ω(nk) | θ(nk) | O(nk) | O(n + k) |
Count Sort | Ω(n +k) | θ(n +k) | O(n +k) | O(k) |
Shell Sort | Ω(n log(n)) | θ(n log(n)) | O(n^2) | O(1) |
Tim Sort | Ω(n) | θ(n log(n)) | O(n log(n)) | O(n) |
Tree Sort | Ω(n log(n)) | θ(n log(n)) | O(n^2) | O(n) |
Cube Sort | Ω(n) | θ(n log(n)) | O(n log(n)) | O(n) |
Algorithm | Time Complexity | ||
---|---|---|---|
Best | Average | Worst | |
Linear Search | O(1) | O(N) | O(N) |
Binary Search | O(1) | O(logN) | O(logN) |
Alan Turing, (born June 23, 1912, London, Eng.—died June 7, 1954, Wilmslow, Cheshire), English mathematician and logician. He studied at the University of Cambridge and Princeton’s Institute for Advanced Study. In his seminal 1936 paper “On Computable Numbers,” he proved that there cannot exist any universal algorithmic method of determining truth in mathematics and that mathematics will always contain undecidable (as opposed to unknown) propositions. That paper also introduced the Turing machine. He believed that computers eventually would be capable of thought indistinguishable from that of a human and proposed a simple test (see Turing test) to assess this capability. His papers on the subject are widely acknowledged as the foundation of research in artificial intelligence. He did valuable work in cryptography during World War II, playing an important role in breaking the Enigma code used by Germany for radio communications. After the war he taught at the University of Manchester and began work on what is now known as artificial intelligence. In the midst of this groundbreaking work, Turing was found dead in his bed, poisoned by cyanide. His death followed his arrest for a homosexual act (then a crime) and sentence of 12 months of hormone therapy.
Following a public campaign in 2009, the British Prime Minister Gordon Brown made an official public apology on behalf of the British government for the appalling way Turing was treated. Queen Elizabeth II granted a posthumous pardon in 2013. The term "Alan Turing law" is now used informally to refer to a 2017 law in the United Kingdom that retroactively pardoned men cautioned or convicted under historical legislation that outlawed homosexual acts.
Turing has an extensive legacy with statues of him and many things named after him, including an annual award for computer science innovations. He appears on the current Bank of England £50 note, which was released on 23 June 2021, to coincide with his birthday. A 2019 BBC series, as voted by the audience, named him the greatest person of the 20th century.
Software engineering is the branch of computer science that deals with the design, development, testing, and maintenance of software applications. Software engineers apply engineering principles and knowledge of programming languages to build software solutions for end users.
Let’s look at the various definitions of software engineering:
- IEEE, in its standard 610.12-1990, defines software engineering as the application of a systematic, disciplined, which is a computable approach for the development, operation, and maintenance of software.
- Fritz Bauer defined it as ‘the establishment and used standard engineering principles. It helps you to obtain, economically, software which is reliable and works efficiently on the real machines’.
- Boehm defines software engineering, which involves, ‘the practical application of scientific knowledge to the creative design and building of computer programs. It also includes associated documentation needed for developing, operating, and maintaining them.’
Successful engineers know how to use the right programming languages, platforms, and architectures to develop everything from computer games to network control systems. In addition to building their own systems, software engineers also test, improve, and maintain software built by other engineers.
In this role, your day-to-day tasks might include:
- Designing and maintaining software systems
- Evaluating and testing new software programs
- Optimizing software for speed and scalability
- Writing and testing code
- Consulting with clients, engineers, security specialists, and other stakeholders
- Presenting new features to stakeholders and internal customers
- Computer Science: Gives the scientific foundation for the software as electrical engineering mainly depends on physics.
- Management Science: Software engineering is labor-intensive work which demands both technical and managerial control. Therefore, it is widely used in management science.
- Economics: In this sector, software engineering helps you in resource estimation and cost control. Computing system must be developed, and data should be maintained regularly within a given budget.
- System Engineering: Most software is a component of a much larger system. For example, the software in an Industry monitoring system or the flight software on an airplane. Software engineering methods should be applied to the study of this type of systems.
An integrated circuit or monolithic integrated circuit (also referred to as an IC, a chip, or a microchip) is a set of electronic circuits on one small flat piece (or "chip") of semiconductor material, usually silicon. Large numbers of tiny MOSFETs (metal–oxide–semiconductor field-effect transistors) integrate into a small chip. This results in circuits that are orders of magnitude smaller, faster, and less expensive than those constructed of discrete electronic components. The IC's mass production capability, reliability, and building-block approach to integrated circuit design has ensured the rapid adoption of standardized ICs in place of designs using discrete transistors. ICs are now used in virtually all electronic equipment and have revolutionized the world of electronics. Computers, mobile phones and other home appliances are now inextricable parts of the structure of modern societies, made possible by the small size and low cost of ICs such as modern computer processors and microcontrollers.
Very-large-scale integration was made practical by technological advancements in metal–oxide–silicon (MOS) semiconductor device fabrication. Since their origins in the 1960s, the size, speed, and capacity of chips have progressed enormously, driven by technical advances that fit more and more MOS transistors on chips of the same size – a modern chip may have many billions of MOS transistors in an area the size of a human fingernail. These advances, roughly following Moore's law, make the computer chips of today possess millions of times the capacity and thousands of times the speed of the computer chips of the early 1970s.
ICs have two main advantages over discrete circuits: cost and performance. The cost is low because the chips, with all their components, are printed as a unit by photolithography rather than being constructed one transistor at a time. Furthermore, packaged ICs use much less material than discrete circuits. Performance is high because the IC's components switch quickly and consume comparatively little power because of their small size and proximity. The main disadvantage of ICs is the high cost of designing them and fabricating the required photomasks. This high initial cost means ICs are only commercially viable when high production volumes are anticipated.
Modern electronic component distributors often further sub-categorize integrated circuits:
- Digital ICs are categorized as logic ICs (such as microprocessors and microcontrollers), memory chips (such as MOS memory and floating-gate memory), interface ICs (level shifters, serializer/deserializer, etc.), power management ICs, and programmable devices.
- Analog ICs are categorized as linear integrated circuits and RF circuits (radio frequency circuits).
- Mixed-signal integrated circuits are categorized as data acquisition ICs (including A/D converters, D/A converters, digital potentiometers), clock/timing ICs, switched capacitor (SC) circuits, and RF CMOS circuits.
- Three-dimensional integrated circuits (3D ICs) are categorized into through-silicon via (TSV) ICs and Cu-Cu connection ICs.
Object Oriented Programming is a fundamental programming paradigm which is based on the concepts of objects and data.
It is the standard way of code that every programmer has to abide by for better readability and reusability of the code.
- Abstraction
- Encapsulation
- Inheritance
- Polymorphism
Read more about these concepts of OOP here
An operating system (or OS for short) acts as an intermediary between the user of a computer and computer hardware. The purpose of an operating system is to provide an environment in which an user can execute programs conveniently and efficiently. An operating system is a software that manages computer hardware. The hardware must provide appropriate mechanisms to ensure the correct operation of the computer system and to prevent user programs from interfering with the proper operation of the system. An even more common definition is that the operating system is the one program running at all times on the computer (usually called the kernel), with all else being application programs.
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First Generation (1945-55): Little progress was achieved in building digital computers after Babbage's disastrous efforts until the World War II era. At Iowa State University, Professor John Atanasoff and his graduate student Clifford Berry created what is today recognised as the first operational digital computer. Konrad Zuse in Berlin constructed the Z3 computer using electromechanical relays around the same time. The Mark I was created by Howard Aiken at Harvard, the Colossus by a team of scientists at Bletchley Park in England, and the ENIAC by William Mauchley and his doctoral student J. Presper Eckert at the University of Pennsylvania in 1944.
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Second Generation (1955-65): The transistor's invention in the middle of the 1950s drastically altered the situation. Computers became dependable enough that they could be manufactured and sold to paying customers with the assumption that they would keep working long enough to conduct some meaningful job. Mainframes, as these machines are now known, were kept locked up in huge, particularly air-conditioned computer rooms, with teams of qualified operators to manage them. Only huge businesses, significant government entities, or institutions could afford the price tag of several million dollars.
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Third Generation (1965-80): In comparison to second-generation computers, which were constructed from individual transistors, the IBM 360 was the first major computer line to employ (small-scale) ICs (Integrated Circuits). As a result, it offered a significant price/performance benefit. It was an instant hit, and all the other big manufacturers quickly embraced the concept of a family of interoperable computers. All software, including the OS/360 operating system, was supposed to be compatible with all models in the original design. It had to run on both extremely big systems, which frequently replaced 7094s for heavy computation and weather forecasting, and tiny systems, which frequently merely replaced 1401s for transferring cards to tape. Both systems with few peripherals and systems with many of peripherals needed to function well with it. It had to function both in professional and academic settings. Above all, it had to be effective for each of these many applications.
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Fourth Generation (1980-Present): The era of the personal computer began with the creation of LSI (Large Scale Integration) circuits, processors with thousands of transistors on a square centimetre of silicon. Although personal computers, originally known as microcomputers, did not change significantly in architecture from minicomputers of the PDP-11 class, they did differ significantly in price.
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Fifth Generation (1990-Present): People have yearned for a portable communication gadget ever since detective Dick Tracy in the 1940s comic strip began conversing with his "two-way radio wrist watch." In 1946, a real mobile phone made its debut and it weighed about 40 kilogrammes. The first real portable phone debuted in the 1970s and was incredibly lightweight at about one kilogramme. It was jokingly referred to as "the brick." Soon, everyone was clamouring for one.
- Convenience: An OS makes a computer more convenient to use.
- Efficiency: An OS allows the computer system resources to be used efficiently.
- Ability to Evolve: An OS should be constructed in such a way as to permit the effective development, testing, and introduction of new system functions at the same time without interfering with service.
- Throughput: An OS should be constructed so that It can give maximum throughput(Number of tasks per unit time).
- Resource Management: When parallel accessing happens in the OS means when multiple users are accessing the system the OS works as a Resource Manager, Its responsibility is to provide hardware to the user. It decreases the load in the system.
- Process Management: It includes various tasks like scheduling and termination of the process. OS manages various tasks at a time. Here CPU Scheduling happens means all the tasks would be done by the many algorithms that use for scheduling.
- Storage Management: The file system mechanism used for the management of the storage. NIFS, CFS, CIFS, NFS, etc. are some file systems. All the data is stored in various tracks of Hard disks that are all managed by the storage manager. It included Hard Disk.
- Memory Management: Refers to the management of primary memory. The operating system has to keep track, of how much memory has been used and by whom. It has to decide which process needs memory space and how much. OS also has to allocate and deallocate the memory space.
- Security/Privacy Management: Privacy is also provided by the Operating system by means of passwords so that unauthorized applications can’t access programs or data. For example, Windows uses Kerberos authentication to prevent unauthorized access to data.
If you are unsure about the difference between memory and storage in computers, this article covers the differences between the two.
The term memory refers to the component within your computer that allows for short-term data access. You may recognise this component as DRAM, or dynamic random-access memory. Your computer performs many operations by accessing data stored in its short-term memory. Some examples of such operations include editing a document, loading applications and browsing the internet. The speed and performance of your system depend on the amount of memory that is installed on your computer.
If you have a desk and a filing cabinet, the desk represents the memory of your computer. Items you need to use immediately are kept on your desk for easy access. However, not much can be stored on a desk due to its size limitations.
Whereas memory refers to the location of short-term data, storage is the component within your computer that allows you to store and access data on a long-term basis. Usually, storage comes in the form of a solid-state drive or a hard drive. Storage houses your applications, operating system and files for an indefinite period. Computers need to write information and read it from the storage system, so the speed of the storage determines how fast your system can boot up, load and access what you’ve saved.
While the desk represents the computer's memory, the filing cabinet represents the storage of your computer. It holds items that need to be saved and stored but is not necessarily needed for immediate access. The size of the filing cabinet means that it can hold a large number of things.
An important distinction between memory and storage is that memory clears when the computer is turned off. On the other hand, storage remains intact no matter how many times you shut off your computer. Therefore, in the desk and filing cabinet analogy, any files that are left on your desk when you leave the office will be thrown away. Everything in your filing cabinet will remain.
In computing, a file system or filesystem (often abbreviated to fs) is a method and data structure that the operating system uses to control how data is stored and retrieved. Without a file system, data placed in a storage medium would be one large body of data with no way to tell where one piece of data stopped and the next began, or where any piece of data was located when it was time to retrieve it. By separating the data into pieces and giving each piece a name, the data is easily isolated and identified. Taking its name from the way a paper-based data management system is named, each group of data is called a "file". The structure and logic rules used to manage the groups of data and their names are called a "file system."
There are many kinds of file systems, each with unique structure and logic, properties of speed, flexibility, security, size and more. Some file systems have been designed to be used for specific applications. For example, the ISO 9660 file system is designed specifically for optical discs.
File systems can be used on many types of storage devices using various media. As of 2019, hard disk drives have been key storage devices and are projected to remain so for the foreseeable future. Other kinds of media that are used include SSDs, magnetic tapes, and optical discs. In some cases, such as with tmpfs, the computer's main memory (random-access memory, RAM) is used to create a temporary file system for short-term use.
Some file systems are used on local data storage devices; others provide file access via a network protocol (for example, NFS, SMB, or 9P clients). Some file systems are "virtual", meaning that the supplied "files" (called virtual files) are computed on request (such as procfs and sysfs) or are merely a mapping into a different file system used as a backing store. The file system manages access to both the content of files and the metadata about those files. It is responsible for arranging storage space; reliability, efficiency, and tuning with regard to the physical storage medium are important design considerations.
A file system stores and organizes data and can be thought of as a type of index for all the data contained in a storage device. These devices can include hard drives, optical drives and flash drives.
File systems specify conventions for naming files, including the maximum number of characters in a name, which characters can be used and, in some systems, how long the file name suffix can be. In many file systems, file names are not case-sensitive.
Along with the file itself, file systems contain information such as the size of the file, as well as its attributes, location and hierarchy in the directory in the metadata. Metadata can also identify free blocks of available storage on the drive and how much space is available.
A file system also includes a format to specify the path to a file through the structure of directories. A file is placed in a directory -- or a folder in Windows OS -- or subdirectory at the desired place in the tree structure. PC and mobile OSes have file systems in which files are placed somewhere in a hierarchical tree structure.
Before files and directories are created on the storage medium, partitions should be put into place. A partition is a region of the hard disk or other storage that the OS manages separately. One file system is contained in the primary partition, and some OSes allow for multiple partitions on one disk. In this situation, if one file system gets corrupted, the data in a different partition will be safe.
There are several types of file systems, all with different logical structures and properties, such as speed and size. The type of file system can differ by OS and the needs of that OS. The three most common PC operating systems are Microsoft Windows, Mac OS X and Linux. Mobile OSes include Apple iOS and Google Android.
Major file systems include the following:
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File allocation table (FAT) is supported by Microsoft Windows OS. FAT is considered simple and reliable, and it is modelled after legacy file systems. FAT was designed in 1977 for floppy disks but was later adapted for hard disks. While efficient and compatible with most current OSes, FAT cannot match the performance and scalability of more modern file systems.
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Global file system (GFS) is a file system for the Linux OS, and it is a shared disk file system. GFS offers direct access to shared block storage and can be used as a local file system.
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GFS2 is an updated version with features not included in the original GFS, such as an updated metadata system. Under the terms of the GNU General Public License, both the GFS and GFS2 file systems are available as free software.
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Hierarchical file system (HFS) was developed for use with Mac operating systems. HFS can also be referred to as Mac OS Standard, and it was succeeded by Mac OS Extended. Originally introduced in 1985 for floppy and hard disks, HFS replaced the original Macintosh file system. It can also be used on CD-ROMs.
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The NT file system -- also known as the New Technology File System (NTFS) -- is the default file system for Windows products from Windows NT 3.1 OS onward. Improvements from the previous FAT file system include better metadata support, performance and use of disk space. NTFS is also supported in the Linux OS through a free, open-source NTFS driver. Mac OSes have read-only support for NTFS.
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Universal Disk Format (UDF) is a vendor-neutral file system used on optical media and DVDs. UDF replaces the ISO 9660 file system and is the official file system for DVD video and audio as chosen by the DVD Forum.
Cloud computing is the ability to access information and applications over the Internet. Cloud computing allows users to access applications and data from any location, as long as they have an Internet connection.
Cloud computing is a type of Internet-based computing that provides shared computer processing resources and data to computers and other devices on demand.
It is a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction.
Machine learning is the practice of teaching a computer to learn. The concept uses pattern recognition, as well as other forms of predictive algorithms, to make judgments on incoming data. This field is closely related to artificial intelligence and computational statistics.
In this machine learning models are trained with labeled data sets, which allow the models to learn and grow more accurate over time. For example, an algorithm would be trained with pictures of dogs and other things, all labeled by humans, and the machine would learn ways to identify pictures of dogs on its own. Supervised machine learning is the most common type used today.
In Unsupervised machine learning a program looks for patterns in unlabeled data. Unsupervised machine learning can find patterns or trends that people aren’t explicitly looking for. For example, an unsupervised machine learning program could look through online sales data and identify different types of clients making purchases.
This trains machines through trial and error to take the best action by establishing a reward system. Reinforcement learning can train models to play games or train autonomous vehicles to drive by telling the machine when it made the right decisions, which helps it learn over time what actions it should take.
Natural language processing is a field of machine learning in which machines learn to understand natural language as spoken and written by humans, instead of the data and numbers normally used to program computers. This allows machines to recognize language, understand it, and respond to it, as well as create new text and translate between languages. Natural language processing enables familiar technology like chatbots and digital assistants like Siri or Alexa.
Neural networks are a commonly used, specific class of machine learning algorithms. Artificial neural networks are modeled on the human brain, in which thousands or millions of processing nodes are interconnected and organized into layers.
In an artificial neural network, cells, or nodes, are connected, with each cell processing inputs and producing an output that is sent to other neurons. Labeled data moves through the nodes, or cells, with each cell performing a different function. In a neural network trained to identify whether a picture contains a cat or not, the different nodes would assess the information and arrive at an output that indicates whether a picture features a cat.
Deep learning networks are neural networks with many layers. The layered network can process extensive amounts of data and determine the “weight” of each link in the network — for example, in an image recognition system, some layers of the neural network might detect individual features of a face, like eyes, nose, or mouth, while another layer would be able to tell whether those features appear in a way that indicates a face.
Web Technology refers to the various tools and techniques that are utilized in the process of communication between different types of devices over the internet. A web browser is used to access web pages. Web browsers can be defined as programs that display text, data, pictures, animation, and video on the Internet. Hyperlinked resources on the World Wide Web can be accessed using software interfaces provided by Web browsers.
- World Wide Web (WWW) The World Wide Web is based on several different technologies : Web browsers, Hypertext Markup Language (HTML) and Hypertext Transfer Protocol (HTTP).
- Web Browser The web browser is an application software to explore www (World Wide Web). It provides an interface between the server and the client and requests to the server for web documents and services.
- Web Server Web server is a program which processes the network requests of the users and serves them with files that create web pages. This exchange takes place using Hypertext Transfer Protocol (HTTP).
- Web Pages A webpage is a digital document that is linked to the World Wide Web and viewable by anyone connected to the internet has a web browser.
- Web Development Web development refers to the building, creating, and maintaining of websites. It includes aspects such as web design, web publishing, web programming, and database management. It is the creation of an application that works over the internet i.e. websites.
The part of a website that the user interacts directly is termed as front end. It is also referred to as the ‘client side’ of the application.
Backend is the server side of a website. It is the part of the website that users cannot see and interact. It is the portion of software that does not come in direct contact with the users. It is used to store and arrange data.
A computer network is a set of computers sharing resources located on or provided by network nodes. The computers use common communication protocols over digital interconnections to communicate with each other. These interconnections are made up of telecommunication network technologies, based on physically wired, optical, and wireless radio-frequency methods that may be arranged in a variety of network topologies.
The nodes of a computer network can include personal computers, servers, networking hardware, or other specialised or general-purpose hosts. They are identified by network addresses, and may have hostnames. Hostnames serve as memorable labels for the nodes, rarely changed after initial assignment. Network addresses serve for locating and identifying the nodes by communication protocols such as the Internet Protocol.
Computer networks may be classified by many criteria, including the transmission medium used to carry signals, bandwidth, communications protocols to organize network traffic, the network size, the topology, traffic control mechanism, and organizational intent.