Skip to main content

Good Read: MSDN Dependency Injection

[PLACEHOLDER]
Dependency Injection (DI) design pattern is a common used design patterns in real-time applications as it allows us to develop loosely coupled software components.
 

Photo by Scott Webb from Pexels - modified by Beolle


You have probably heard about the Factory Pattern and the separation between the interface and the implementation using services, where the client objects are often responsible for service location.
The Dependency Injection pattern is a particular implementation of Inversion of Control. Inversion of Control (IoC) means that objects do not create other objects on which they rely to do their work. Instead, they get the objects that they need from an outside source (for example, an xml configuration file).
Dependency Injection (DI) means that this is done without the object intervention, usually by a framework component that passes constructor parameters and set properties."

Paragraph from articleASP.NET MVC 4 Dependency Injection

Fantastic read about these patterns at MSDN location.

Recommend both links.

Trending posts

Steer for a talent transformation strategy (and avoiding AI fatigue)

 There was a debate on whether to feature the term “AI” in the title of this article. Honestly, a key motivation for pursuing the research that led to this post was sparked by the widespread excitement about AI appearing constantly in our LinkedIn feed, to the point of feeling the fatigue, and even a bit disappointed in the algorithm of this, and the others, social media and content curated apps.  We soon discovered that there is an entire concept called "AI fatigue", not exactly how we were feeling it, but more about the mixed emotions people in the workforce have regarding the use of AI tools. Photo by Mart Production via Pexels (background updated with AI and Adobe  tech) From micro blog posts to video podcasts, lately, most of the tech content we encounter revolves around AI. They often sound or read very similar, usually mentioning the same few top providers. The articles (and social posts... at least the popular ones with paid-campaigns behind it) tend to focus less...

Reimagining Digital Experience Management: How Agentic AI is Transforming Adobe Experience Manager

 Adobe Experience Manager (AEM) has introduced powerful new Agentic AI capabilities designed to continuously improve and adapt digital experiences at the speed of AI. By integrating advanced AI orchestrators through Agent-to-Agent (A2A) and Model Control Protocol (MCP) tools, AEM enables brands to automate complex workflows and enforce compliance seamlessly across enterprise ecosystems. Through a suite of specialized agents, teams can transition from manual, weeks-long processes into fast, AI-assisted workflows powered by simple natural language prompts. Photo by Tunahan KALAYCI via Pexels   Here is a breakdown of the key agents driving AEM’s new Agentic capabilities, their value propositions, their guardrails, and their current availability status. 1. Brand Experience Agent. Overview. The Brand Experience Agent accelerates digital modernization through specialized sub-agents—the Experience Modernization Agent, Experience Production Agent, and Experience Development Agent. Tog...

Designing Habit Forming Mobile Application

Mobile Applications have become an integral part of our daily lives - we use mobile apps as alarm clocks to wake us up in the morning, to create to do lists when we start our day, to communicate with our colleagues at work via apps like Skype. We even check reviews of restaurants to visit on apps like Yelp and we seek entertainment on apps like Netflix and spotify. So what drives us to use these apps so seamlessly in our daily lives? Why we prefer some apps over others? Is there a science behind designing successful mobile apps like Facebook?  Photo by Peter C from Pexels A study in US revealed that a user between the age of 18 and 44 visits the Facebook app on average 14 times a day [1]. This shows that using the Facebook app is a daily routine for many of its users. This makes Facebook a great example of a habit forming mobile app which is designed with human psychology in mind that encourages habit forming behavior in its users .   I recently attended a seminar ...

Assembling MLOps practice - part 1

In one of our previous articles it was highlighted how DevOps manages the End-to-End application cycle, leveraging agility and automation. CI/CD pipelines, collaboration and transparency, monitoring and automation are part of the list on how DevOps leverages and facilitates agility. What if then we bring those to support ML? That is how MLOps comes to the table and starts making sense! Lego Alike data assembly - Generated with Gemini A big tech corporation, or a startup, nowadays will see how it is becoming a requirement to incorporate AI and Machine learning (ML) in their operations. ML components are key parts of the ecosystem, supporting the solutions provided to clients. As a result, DevOps and MLOps have become part of the "secret sauce" for success.  What is MLOps Just to bring the definition of what you probably know (or put together based on the above) MLOps focuses on the life-cycle management of machine learning models. It combines machine learning with traditional ...

This blog uses cookies to improve your browsing experience. Simple analytics might be in place for pageviews purposes. They are harmless and never personally identify you.

Agreed