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 Agile Application Life Cycle Management (Agile ALM)?

TechDogs Avatar

Agile application life cycle management, or agile ALM, is a software development technique that aims to improve a product's quality over its life cycle while keeping the development time as low as possible. You can assume it like this Imagine you're building a house. You want it to be robust and stable, but you also want it to be the most beautiful house on your block. How do you get there? You need an experienced architect who knows how to build sturdy houses that look great, and you need someone who can ensure that a home gets built as quickly and efficiently as possible. That's agile ALM in a nutshell: It's about finding the best way to create software that works well while also being developed in as short a time as possible. Agile ALM is like the Starbucks of ALM. It's not quite a latte, but it's more than just coffee. Agile ALM is designed to provide an integrated approach to application lifecycle management (ALM) by supporting agile values, frameworks and strategies within the application lifecycle. It does this by increasing collaboration among stakeholders and providing an integrated approach to ALM by improvising the people side of application development. Some key components/phases of an agile ALM include collaborative development, task-based development, functional and technical release management, quality assurance and stakeholder focus. The best thing about agile ALM is that it's open-source, so you can add to it and make it your own. Do you know what the best part about open-source software is? It's that you don't have to buy it! You use it. If something is missing, you can add it yourself. If you've ever had a house built from scratch or even just put together furniture from Ikea, you know that sometimes things don't work out exactly like they're supposed to. With an open-source system, you have no problem adding on until everything fits perfectly into place and looks great!

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

Autonomous Things

Autonomous Things, or #AutonomousThings & AuT for short, are like robots that can think for themselves. They're machines that can sense their environment, make decisions, and take action without human intervention. Like how you can tell your robot vacuum cleaner to clean your room, Autonomous Things can be programmed to perform specific tasks. Some examples of Autonomous Things include self-driving cars, drones, and industrial robots. These machines are equipped with sensors, cameras, and other technologies that allow them to understand and navigate their surroundings. They also have rules or algorithms that dictate how they should behave in different situations. One of the main advantages of Autonomous Things is that they can operate 24/7 without getting tired or making mistakes. This makes them ideal for tasks that are dangerous or tedious for humans to perform, such as inspecting pipelines or exploring the deep sea. Additionally, Autonomous Things can collect and analyze large amounts of data, which can help decision-making and improve overall efficiency. However, they also present some concerns, including safety and security difficulties, privacy concerns, and ethical questions about their influence on jobs and society. These are only some of the problems that can be raised. For instance, a self-driving car needs to be able to make split-second judgments in the event of an emergency to guarantee the well-being of all its passengers and the safety of pedestrians and other motorists on the road. When autonomous items are connected to the internet, there is a potential for hacking and other cyberattacks, which raises concerns over data security. In short, #AutonomousThings are machines that can think for themselves, sense their environment, make decisions, and take actions without human intervention, such as self-driving cars, drones, and industrial robots. They have advantages such as operating 24/7, collecting and analyzing large amounts of data and being useful for dangerous or tedious tasks. However, they also raise some safety, security and ethical questions. #Autonomousvehicles #drones #industrialRobots

...See More

Real Reality (RR)

The word "Real Reality" describes the objective reality that exists independently of our subjective thoughts, feelings, and experiences. In this context, "Real Reality" (or "RR") is an acronym. It's the world, unfiltered and untainted by personal preferences. The real reality is what you'd get if you had a camera that could capture every angle and every detail without distorting them. This is the unvarnished truth; no embellishment is allowed. The term "realistic rendering" (RR) is used in information and communications technology to describe creating an environment that is faithful to the real one. Virtual reality, augmented reality, and mixed reality are all examples of this category; they all attempt to immerse the user in a convincing simulation. Also included are holograms and similar technologies. RR is related to the "hard issue of consciousness" in philosophy and psychology. The question of why and how people have subjective experiences is at stake here. It is argued here that our minds create the world we experience and that this experience differs from the actual world. Skepticism, related to RR, holds that our knowledge of the world is limited and that our opinions about it should be tentative and open to revision. In a nutshell, when people refer to "actual reality," they mean the objective truth of the world, which exists independently of our subjective perspectives and interpretations. It's taking pictures of the world as it is without imposing one's ideas or biases on it. One of the main goals of IT is to create an environment that is a faithful representation of the real one. This relates to the difficult issue of self-awareness and skepticism in philosophical studies. The only way to come closer to Real Reality is to keep a healthy dose of skepticism while simultaneously having an open mind. #RealRealityCheck #RealReality #ObjectiveReality #Perception #Truth #VirtualReality #AugmentedReality #MixedReality #Philosophy #Psychology #Skepticism

...See More

Typeof Operator

You might think of #Typeof as the Sherlock Holmes of JavaScript. Can you imagine working on a JavaScript project and not knowing what kind of data you're dealing with? The #Typeof operator will come to the rescue, so don't worry! The JavaScript operator #Typeof returns a string representing the variable's type. Put another way, and it acts as a detective in the data investigation process. Consider the case when you need to determine the data type of the variable x. Enter a type of x, and the desired output will appear. It doesn't matter if the variable is a string, a number, a boolean, or even undefined; JavaScript will return the kind of data contained in the variable. No, there's more where that came from! As intriguing as #Typeof already is, it has its unique features. For instance, it gives back "objects" for objects, even though not all things are identical. For example, arrays are objects in JavaScript, and the #Typeof operator will also return "object" for arrays. Instanceof the operator and other methods should be used to tell arrays and objects apart. #Typeof's return of "function" for functions is also unusual and can be either misleading or helpful depending on the circumstances. In JavaScript, a function is an object. However, unlike regular objects, functions have several unique features and behaviors. Lastly, the #Typeof operator is helpful for testing and troubleshooting code. If you have a line of code that should return a particular data type, you can use the #Typeof operator to verify that the value returned matches your expectation. To summarize, the #Typeof operator is useful software for JavaScript programmers. In the context of debugging and troubleshooting code, knowing the data type can be invaluable. Remember that the #Typeof operator is available to assist you the next time you're working on a project and need to determine the nature of the data at hand.

...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