We use essential cookies to make our site work. With your consent, we may also use non-essential cookies to improve user experience, personalize content, customize advertisements, and analyze website traffic. For these reasons, we may share your site usage data with our social media, advertising, and analytics partners. By clicking ”Accept,” you agree to our website's cookie use as described in our Cookie Policy. You can change your cookie settings at any time by clicking “Preferences.”
Lead the Pack Awards 2025

CLICK HERE Know more about the Lead the Pack Awards 2025

What Is Behavior Driven Development (BDD)?

TechDogs Avatar

It's not just a way to communicate with your team. It's a way of life. Behavior Driven Development (BDD) is a method for developing software using a cycle of testing, design, and production phases. BDD aims to produce software that accurately reflects the needs and desires of its end users. The BDD approach helps us understand the problems we are trying to solve with our software by focusing on the behavior or actions of users rather than on the implementation details of the system itself. BDD helps us to focus on what our users want from a product rather than how it should be built. Behavior-Driven Development is about specifying software as system behaviors rather than just code. Behavior-Driven Development (BDD) helps software teams better understand what they're developing by focusing on behavioral specifications for each software unit under development. It is the most recent and exciting development in software development. It was inspired by the increasingly popular agile software development approach, emphasizing early customer involvement and frequent iteration. BDD aims to establish a clear link between business goals, customer requirements and the technical details of software development. This allows for more effective communication between different parts of an organization, resulting in better products and happier customers. BDD works by associating business outcome as a "story" or specification that defines its requirements, business benefits and standard testing methodology used to ascertain the completion of a software unit. In BDD, we know that the best way to build a successful app is to ensure everyone's on the same page. That's why BDD created a two-class system for our stakeholders, core and incidental. Core stakeholders focus on business objectives, outcomes, and application behavior. They're the ones who make sure your app is going to get you where you want to go. Incidental stakeholders are functional and non-functional people working to provide the desired application behavior and outcome. These are the people who ensure your core stakeholders' needs are met—whether they're programmers, project managers, or anything in between!

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

Trending Definitions

Immutable Type

Immutable types, also known as "constant types," are like the strong, silent types of the programming world. They're the ones that never change, never falter, and always stay the same, like that friend who always shows up to your parties with the same hairstyle. In programming, an immutable type is a data type whose value cannot be modified after it's been created. For example, when you create a string, you can't change or add more letters. Once it's created, it's set in stone. This might seem a bummer at first, but trust me, and it's actually a good thing. Immutable types are great for situations where you want to ensure that a certain value doesn't change, like when you're working with important data or programming something that needs to be predictable. One of the most common immutable types is the string. In many programming languages, a string is an immutable type, which means that once you create it, you can't change it. For example, let's say you create a string called "hello world." Once it's created, you can't change the letters or add more letters to it. It will always be " hello world." Another common immutable type is the tuple. A tuple is like a list, but it's immutable. Once you create it, you can't add or remove items. It's a fixed collection of items that stays the same. Immutable types can be helpful in situations where you want to ensure that a value doesn't change. For example, when working with essential data, you want to ensure that the data remains the same. And when you're programming something that needs to be predictable, you want to ensure that the value doesn't change unexpectedly. Immutable types also have performance benefits. For example, when working with a large amount of data, you can use an immutable type to prevent that data from being modified. This means that you don't have to make a copy of the data, which can save memory and processing power. To sum it up, immutable types are like the strong, silent types of the programming world. They're the ones that never change, never falter, and always stay the same. They're helpful in situations where you want to ensure that a value doesn't change, like when you're working with important data or programming something that needs to be predictable. And they also have performance benefits, like saving memory and processing power. So, next time you're programming, don't be afraid to use immutable types. They'll be your rock-solid friend.

...See More

Thousands of Lines of Code (KLOC)

When buying a new car, it's essential to know how many miles per gallon it gets. When purchasing a new house, it's necessary to know how many square feet it has and when you're looking to buy software, it's essential to know how many lines of code it has. The number of lines of code is always measured, which is used to evaluate the software size. KLOCs are always used to estimate the required time for a team to build a project. The lower the KLOC, the less time it takes for your team to make the product—which means you can get your product out there and generate revenue sooner. When you think about it, it's pretty silly to try and measure developer productivity by lines of code. That's not how developers work. For example, if I were a factory worker, I'd be able to tell you exactly how fast I could make widgets. It would be like, "If I work at this pace and produce this many widgets in an hour, then I'm doing great!" but, if I were a software developer and someone asked me how many lines of code I wrote in an hour? Well, that would be silly. Because writing code is only part of what we do as developers, we also have to test our code—sometimes, we need to refactor it and rewrite it entirely! So, if we're being paid based on how many lines of code we write per hour. Wwhat happens when we need to take time away from writing new code to fix bugs or improve our existing codebase? And what happens when we want to write tests first before starting any coding work? If all those things are considered "non-development" work, then we're not being paid for our development time!

...See More

Neuro Symbolic Artificial Intelligence

The term "Neuro Symbolic Artificial Intelligence" (NSAI) is a mouthful that describes the ideal union of human-like intuition for making decisions and the efficiency of computers. Put another way, it's the same as if a human brain were connected directly to a powerful computer. Imagine a supercomputer capable of analyzing data and performing calculations at lightning speed but lacking a human's intuitive and deductive reasoning abilities. That's where NSAI comes in. It's a way to build intelligent systems that can comprehend and make sense of complex data by leveraging the strengths of both machine learning algorithms and human cognition. Finding that sweet spot where AI and human intellect can work together is the goal of NSAI. The goal is to build intelligent machines that can reason, learn, and think like humans while efficiently processing massive amounts of data in real time. Knowledge representation, simplifying complex concepts into more manageable chunks, is central to NSAI. The metaphorical meaning of NSAI becomes apparent here. In this context, "representation" refers to using rules and symbols to encode information in a form that a computer can understand. NSAI, however, makes use of more than just signs and regulations. Furthermore, it uses neural networks, a form of machine learning algorithm with the ability to acquire knowledge from experience and modify its behavior accordingly. At this point, we can talk about the "neuro" component of NSAI. NSAI can develop intelligent and adaptable systems by integrating the two methods. NSAI's significance, then, begs the question: why? This development may forever alter how we tackle complex healthcare, banking, and transportation issues. With NSAI, we can design systems to sift through mountains of data, identify patterns, and make informed recommendations for action. In the medical field, for instance, NSAI might be used to create individualized treatment programs for patients in light of their specific conditions and genetic makeup. Its potential application in finance lies in detecting trends and patterns in financial data that inform informed investment choices. Finally, NSAI has the potential to improve transportation through the creation of more innovative traffic control systems. To sum up, NSAI is a promising and exciting area since it merges the finest of AI with that of humans. The goal is to build computerized systems that mimic human cognitive abilities such as learning, reasoning, and adaptability. One day we might even be able to use NSAI to construct the ultimate super-intelligent robot!

...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.

Home

Hot Topic: AI

News

Articles

Branded Insights

  • Dark
  • Light