What Is Beginner's All-Purpose Symbolic Instruction Code (BASIC)?

TechDogs Avatar

Beginner's All-Purpose Symbolic Instruction Code (BASIC) is like a language for dummies. It's a subset of the English language, and it's made up of only words that are easy to understand, like "print," "printer," and "keyboard". BASIC was invented by John Galt in 1964, who thought it would be a good idea to make programming easy for everyone to learn. The original goal of BASIC was to teach children how to program computers so they could eventually become millionaires. BASIC is a programming language developed by Dartmouth College's Thomas Kurtz and John Kemeny to give students the ability to write programs for the school's time-sharing system. The language was released in 1964 and has remained a popular option for non-technical users ever since. BASIC is known for its simple syntax, which allows users to write code without knowing much about computer science. Dartmouth College was one of the first schools to start using computers for research and teaching purposes, so BASIC was developed as an accessible way for students with a minimal technical background to learn how to program. QBasic was a BASIC variant, and it's still commonly used today. It's also sometimes called QuickBASIC. The most common version of QBasic is QuickBASIC for DOS, which was released in 1985. It was based on earlier BASIC versions developed at Dartmouth College in 1964 and then ported to other computers. VB is another popular programming language that has been used since the 1980s. It's typically used with Microsoft Visual Studio and other development tools and has a GUI and object-oriented features. Unfortunately, although BASIC has been around for over 50 years, it hasn't helped most children get rich yet. (In fact, most adults don't even know what BASIC is.) Still, millions of people have learned the basics of programming through BASIC—and if you're starting with this stuff yourself, then we hope you'll give us a chance!

TechDogs Logo

Related Terms by Software Development

Sentiment Analysis

Sentiment analysis is a lot like having the ability to discern minds, except it's done with computers. Opinion mining is a data mining subfield that utilizes unstructured text analysis to gauge consumer sentiment toward a brand, individual, or concept. Sentiment analysis is a technique for gleaning emotional data from online sources using NLP, computational linguistics, and text analysis. Social media sites and other online forums where users post their thoughts and observations on various subjects are familiar places to find this data. Sentiment analysis uses complex algorithms and machine learning methods to identify a person's opinion's positive, negative, or neutral nature. As a bonus, it can determine whether the text is joyful, sad, angry, or anxious, as well as other emotions. The results of this analysis can be used to calculate the extent to which the public approves or disapproves of various brands, individuals, and concepts. Knowing the thoughts and preferences of customers can be invaluable to companies and organizations. A business may employ mood analysis to monitor customer feedback via social media and use the results to improve its offerings. The material's polarity in its context can also be revealed through sentiment analysis. It can tell you how people feel about a subject or entity and what it is about that subject or entity that people like or dislike. Sentiment analysis can show, for instance, that consumers have a generally positive attitude toward a given brand but a negative attitude toward its customer service. To sum up, sentiment analysis is a subfield of data mining that assesses consumer reaction to a brand, individual, or concept by examining written language. It's like having the ability to read thoughts, only this time, and it's accomplished through complex mathematical formulas stored in a computer. Sentiment analysis, or opinion mining, is a method for gleaning and analyzing biased data from online sources, such as social media and blogs. Data analysis can reveal the contextual polarity of information and provide quantitative estimates of the public's feelings or responses to specific goods, people, or ideas.

...See More

Self-Provisioning

If you're like most people, you're always looking for ways to get out of work. So when we heard about self-provisioning—the ability to set up services and applications by yourself without the help of a dedicated IT specialist or service provider—we were all over it. It's like having your server, except that instead of having to buy your server, pay for its maintenance, and hire an IT person to manage it when things go wrong, you sign up with a cloud provider who has already done everything for you. Moreover, they'll even let you use their servers for free! So if you have ever wanted to launch your website but didn't want to take on the burden of managing it yourself, or if you've been dreaming of starting an online business but didn't want to spend all that money on servers and software licenses well, now's your chance! Self-provisioning is excellent, but the self-de-provisioning part is even more significant. Provisioning is like getting a massage—you know what you want and are in charge of getting it. Deprovisioning is like getting a haircut—it's a little more complicated than telling someone what to do. It requires much attention to detail and technical skill to ensure you're not cutting off any substantial parts of yourself in your zeal to be smooth and sleek. We don't want you to be soft and elegant! We want you to be well-groomed! So here are some tips for taking care of yourself by taking care of your resources. Always deprovision after using a resource so that others can use it when they need it later. Only do something once you've found another that does what that other one did for you (and then de-provision the old one).

...See More

Secure Hash Algorithm (SHA)

Secure Hash Algorithm is a set of algorithms developed by the National Institutes of Standards and Technology and other government and private parties. Cryptographic hashes (or checksums) have been used for electronic signatures and file integrity for decades. However, these functions have evolved to address some of the cybersecurity challenges of the 21st century. The NIST has developed a set of secure hashing algorithms that act as a global framework for encryption and data management systems. The initial instance of the Secure hash Algorithm (SHA) was in 1993. It was a 16-bit hashing algorithm and is known as SHA-0. The successor to SHA-0, SHA-1, was released in 1995 and featured 32-bit hashing. Eventually, the next version of SHA was developed in 2002, and it is known as SHA-2. SHA-2 differs from its predecessors because it can generate hashes of different sizes. The whole family of secure hash algorithms goes by the name SHA. SHA-3, or Keccak or KECCAK, is a family of cryptographic hash functions designed by Guido Bertoni, Joan Daemen, Michaël Peeters, and Gilles Van Assche. SHA-3 competition to develop a new secure hash algorithm was held by the United States National Security Agency (NSA) in 2007. To be a super safe and fast hashing algorithm, SHA3 was developed from this contest. The evolution of cybersecurity has led to the development of several "secure hash algorithms." Security is a crucial concern for businesses and individuals in today's digital world. As a result, many types of encryption have been developed to protect data in various scenarios. One of these is hash algorithms. All secure hash algorithms are part of new encryption standards to keep sensitive data safe and prevent different types of attacks. These algorithms use advanced mathematical formulas so that anyone who tries to decode them will get an error message that they aren't expected in regular operation.

...See More

Related White Papers On Software Development

Related News On Software Development

Related Events & Webinars On Software Development

Trending Definitions

Peltier Effect

When a current is conducted through particular kinds of substances, such as semiconductors, a phenomenon known as the Peltier Effect occurs, which results in the phenomenon known as the Peltier Effect. This event, which appears to be caused by magic, can be explained by scientific principles. When an electric current is passed through a semiconductor device, it is possible for there to be a temperature difference on either side of the device. This can happen because the device conducts heat differently. The term "Peltier heat pump" is what people in the industry used to refer to this particular variety of heat pumps. The side of the semiconductor where the electricity flows in will become warmer as the semiconductor conducts electricity. In contrast, the semiconductor's side, where the electricity flows out, will become colder as the semiconductor conducts electricity. This is the epitome of the Peltier effect in action, and it couldn't be more precise! Now that we have a general understanding of the situation, let's dive into some finer details. When an electric current travels between two electrical conductors or semiconductors that are not chemically or physically identical, a phenomenon known as the Peltier effect occurs. This effect is named after the scientist who discovered the phenomenon. Due to this, a temperature difference occurs at the junction of the two materials as a result of what has happened. The transmission of heat from one material to another is the root cause of this phenomenon. The scientist responsible for making the initial discovery of it is also credited with naming it the "Seebeck effect," another name. This name is said to be expected in some circles. In a nutshell, the Peltier effect primarily concerns the passage of electric current and thermal energy. It is an exciting piece of scientific research that has the potential to be employed in a wide variety of contexts, such as the cooling of electronic equipment and even in thermoelectric generators. This might be very significant in the future. #PeltierEffect #Thermoelectrics #HeatPump #SeebeckEffect #Semiconductors

...See More

Information Hiding

When it comes to information hiding, programmers are like the vampires of the programming world—they need their blood. They feed on it, and they want more of it. Information hiding is a way for programmers to get their fix: it allows them to hide certain parts of their code from other people who might want to change it. Information Hiding for Programmers Information hiding is not an easy thing for programmers to do. It's not just about putting things in folders or writing code with lots of comments—it's about ensuring that you're saying the right thing when you expose something in your program code. Programmers know that if they reveal too much data, they'll have to make changes more often than they like because someone will come along and try to change things outside the scope of their original work. But suppose they don't expose enough data. In that case, they'll have trouble making changes later on down the road when they realize it needs something more than what they initially thought they needed when building out their software application or website design project! Information hiding can also be defined as increasing abstraction and modularity, making it easier to maintain and extend programs. Information hiding is the process of hiding implementation details from other modules and clients and, at the same time, making those details accessible to other modules through well-defined interfaces. In other words, information hiding provides a level of abstraction between what clients see and what is happening behind the scenes. One advantage of information hiding is yielding flexibility, allowing a programmer to modify a program more readily. It also may be done by placing source code within modules for easy access in the future as the program develops and evolves. In addition, it can make it easier to understand the code by dividing it into separate parts. It may include separating different modules from each other into additional files or classes.

...See More

Pipelining

Pipelining is a tactic used in computer architecture and processing to improve the effectiveness and speed of data processing. Pipelining is also known as "streaming." This is performed by utilizing several pipelines in parallel with one another. The 1970s were a pivotal decade for the advancement of pipeline technology. Setting up a pipeline-like series of processing stages is an essential feature of the method. Each pipeline level processes a subset of the data before sending it on to the stage that comes after it in the pipeline. Instead of waiting until one piece of data has been entirely processed before moving on to the next, it is now possible to process a large amount of data simultaneously. This is made feasible due to the availability of multitasking, which has recently come into existence. Think of it as being similar to an assembly line at a factory, where each worker is responsible for completing a specific duty before passing the product on to the next worker in the line. In this scenario, the product is being assembled. In this case, the product is being put together after being purchased. Since this is now possible, it is possible to manufacture several different goods simultaneously, which improves both productivity and velocity. Similarly, the utilization of pipelining in the processing of computer data enables a variety of other pieces of data to be processed simultaneously, which in the end, reduces the amount of time necessary for the processing. In the context of contemporary computer processors, the phrase "pipelining" refers to a frequently used technique. In this method, instructions are broken down into individual stages, and those phases are processed in parallel. As a result, it is feasible to process a very la huge of instructions simultaneously, which increases processing speed and efficiency.

...See More

Trending Articles

Join Our Newsletter

Get weekly news, engaging articles, and career tips-all free!

By subscribing to our newsletter, you're cool with our terms and conditions and agree to our Privacy Policy.

  • Dark
  • Light