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Java Technology

  • 08/5/2022

  • Dr.Yazdani Hasan

1. Java is easy to learn Every programming language comes with a learning curve, but Java shares many similarities with C, C++ and JavaScript. Anyone with experience in any of those languages will pick up Java syntax quickly. Java also has a very rigid and predictable set of rules that govern code structure. This contrasts starkly with other, untyped scripting languages where it seems like anything goes. When you try to master a new programming language, a clear set of consistently enforced rules makes learning easier. Furthermore, when things don't make sense, programmers new to Java can find a strong support network of YouTube videos, websites like StackOverflow and online forums like CodeRanch to find answers to a multitude of questions. 2. The rich set of Java APIs The Java API is extensive. The standard JDK comes with over 200 built-in packages containing Java APIs that allow for everything from parsing XML to translating between time zones. When developers add on the Jakarta EE APIs, they have an even more extensive library of APIs that allow for the development of complex, middle-tier applications and cloud-native microservices. But the rich ecosystem of Java APIs extends far beyond those sanctioned by Oracle or provisioned through Jakarta. For data persistence, there's the JBoss Hibernate project. For cloud-native microservices development in Java, there's the full suite of Spring Boot APIs. And of course there's a multitude of open source Apache API projects that address a wide range of software development use cases, from aggregating error messages with log4j to solving complicated problems with HashMaps and fail-safe Iterators through the Apache Commons Collections API. The rich set of Java APIs available to developers aid in the development of strong, error-free applications. 3. Java's tool ecosystem The application development landscape is filled with software development tools written in Java -- by Java developers -- that are designed to simplify and streamline the development, deployment and even decommissioning of Java applications. A few examples of tools written in Java include: Gradle: an incredibly powerful, open source build tool Maven: an open source tool designed to solve dependency management problems Jenkins: a Java-based continuous integration and delivery tool This is by no means an exhaustive list of Java's tool ecosystem. Other examples of tools and technologies written in Java include application servers like Tomcat to Red Hat's popular, Kubernetes-native Java stack named Quarkus. Google did copy over 11,500 lines of code from the Java Standard Edition when they built their Java clone. As a result, developers can expect that the version of Java they see on Android is pretty close to the original. If you know can write Java code for desktop or server-side applications, you'll pick up Android development very quickly. The low-level differences between the JVM and the Dalvik Android Runtime will all be pleasantly abstracted away from you after a brief learning curve. When developers learn Java, the entire Android ecosystem will be at their disposal. 5. Forward evolution with backwards compatibility Java evolves slowly, but it does evolve. With over 25 years of evolution, Java has plenty of evolutionary improvements to be proud about. From the bulletproof modularity system that was delivered as part of Project Jigsaw, to the recently added ability of functional programming in Java with lambda functions, Java continues to implement big changes that the community demands. Incremental additions in non-LTS releases, such as the the addition of the new Record data typeand garbage collectors for improved memory management, showcase that the JDK is also constantly evolving. But in the enterprise software development world, backwards compatibility is just as important as adding new features. Java has always made this a top priority for the stewards of the language. Very rarely does a comprehensive update or feature addition create issues with code written against older releases. I personally compiled and packaged some complicated code that was written 20 years ago, and it ran without any issues on the latest Java 17 release. When enterprise clients know that things won't break when they perform a JVM upgrade, it gives just another reason why they choose to stick with Java as the best programming language.

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PHP Vs Javascript: The Right Tech For Your Next Big Project

  • 08/5/2022

  • Dr.Yazdani Hasan

If someone says “JavaScript is only for front end development, and PHP is for back end” — do not listen. Before I jump into claiming that one language is better than the other, there is something I need to clarify. I don't want to turn the PHP vs JavaScript discussion into comparing apples and oranges, so I should explain the main difference between JavaScript and PHP. PHP is a programming language for back end development only. JavaScript, in turn, was initially designed as a front end development language. But with the introduction of Node.js in 2009, JavaScript became full stack. The commonly cited claim that “JavaScript is only for front end development, and PHP is for back end” is just not true. Today, you can develop the entire app with JavaScript, both client side and server side. The question is, which language is more effective for your particular project?

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Steps to Become an Outstanding Java Developer

  • 12/5/2022

  • Dr.Yazdani Hasan

1. Have a strong foundation and understanding of OO principles For a Java developer, having a strong understanding of object-oriented programming is a must. Without having a strong foundation on OOPS, one can't realize the beauty of an object-oriented programming language like Java. If you don't have a good idea of what OOPS is, even though you are using the OOP language, you may be still coding in a procedural way. Just studying OO principle definitions won't help much. We should know how to apply those principles in designing a solution in an OO way. So, one should have a strong knowledge of object modeling, inheritance, polymorphism, design patterns, etc. 2. Master the core APIs It doesn't matter how strong you are in terms of theoretical knowledge if you don't know the language constructs and core APIs. In the case of Java, one should have very strong hands-on experience with core APIs like java.lang.*, I/O, exceptions, collections, generics, threads, JDBC, etc. When it comes to building web applications, no matter which framework you are using, it's also crucial that you understand concepts around servlets and JSPs — this is a must. 3. Keep coding Things look simpler when talking about them theoretically. We can give a solution to a problem very easily in theory. But we can realize the depth of the problem when we start implementing our approach. You will come to know the language limitations, or design best practices while coding. So keep coding. 4. Subscribe to forums We are not alone. There are lots of people working on the same technologies that we are working on. While doing a simple proof of concept on a framework may not give you real challenges, when you start using it on real projects, you will face weird issues and won't find any solution in their official documentation. When starting to work on new technology, the best and first thing to do is subscribe to relevant technology forums. Whatever the issue you are facing, someone else in the world might have already faced it and found the solution. And it would be really really great if you could answer the questions asked through other forum users. 5. Follow blogs and respond As I already told, you are not alone. There are thousands of enthusiastic technology freaks around the world blogging their insights on technology. You can also gain valuable perspectives on the same technology from other blogs and developers. Some may find specific framework features to be exceptionally useful, while other's might find those features stupid and pointless, giving his own reasons of why he felt like that. So you can see both the good and the bad from other developers using those tools. Another way to gain value from looking at other blogs is to respond/comment on posts with your opinions and questions. 6. Read open-source frameworks' source code A good developer will learn how to use a framework. But if you want to be an outstanding developer, you should study the source code of various successful, popular frameworks where you can see the internal working mechanism of the framework as well as best practices. It will help a lot in using when using frameworks in a more effective way. 7. Know the emerging technology trends In terms of open-source software development trends, they are growing tremendously. By the time you get a good idea on how to use a specific framework, it risks becoming obsolete as some new framework comes into the picture with super-set of features. Then, the problem you are trying to solve with your current framework may be already solved more easily by the new framework with a single line of configuration. So, keep an eye on what's coming in the picture, and what's going out. 8. Keep commonly used code snippets/utilities handy Over time, you may need to write/copy-paste the same piece of code/configuration again and again. Keeping those kind of configuration snippets like log4.properties, JDBC configuration, etc. and utilities like StringUtils, ReflectionUtils, DBUtils will be more helpful. I know it, itself, won't make you an outstanding developer. But just imagine some co-developer asks you to help in fetching the list of values of a property from a collection of objects, and then you just used your ReflectionUtil and gave the solution in a few minutes: That will make you outstanding. 9. Know different development methodologies Be familiar with various kinds of methodologies like Agile, SCRUM, XP, Waterfall, etc. Nowadays, choosing the development methodology depends on the client. Some clients prefer Agile and some clients are happy with the Waterfall model. S,o having an idea on various methodologies would be a real plus. 10. Document/blog your thoughts on technology In a day-to-day job, you may learn new and better ways of doing things, as well as best practices, architectural ideas, etc. Keep documenting those thoughts, blog about them, and/or share them across the community. Imagine you solved a weird problem that occurred while doing a simple POC and you blogged about it. Maybe developers elsewhere in the world are facing the same issue on a production-deployed application. Think of how valuable that solution is to that developer. So, blog your thoughts, they might be helpful for others or to yourself one day!

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Artificial Intelligence Importance

  • 30/5/2022

  • Mr Maruti Maurya

What is artificial intelligence (AI)? rtificial intelligence is the simulation of human intelligence processes by machines, especially computer systems. Specific applications of AI include expert systems, natural language processing, speech recognition and machine vision. How does AI work? As the hype around AI has accelerated, vendors have been scrambling to promote how their products and services use AI. Often what they refer to as AI is simply one component of AI, such as machine learning. AI requires a foundation of specialized hardware and software for writing and training machine learning algorithms. No one programming language is synonymous with AI, but a few, including Python, R and Java, are popular. In general, AI systems work by ingesting large amounts of labeled training data, analyzing the data for correlations and patterns, and using these patterns to make predictions about future states. In this way, a chatbot that is fed examples of text chats can learn to produce lifelike exchanges with people, or an image recognition tool can learn to identify and describe objects in images by reviewing millions of examples. AI programming focuses on three cognitive skills: learning, reasoning and self-correction. Learning processes. This aspect of AI programming focuses on acquiring data and creating rules for how to turn the data into actionable information. The rules, which are called algorithms, provide computing devices with step-by-step instructions for how to complete a specific task. Why is artificial intelligence important? AI is important because it can give enterprises insights into their operations that they may not have been aware of previously and because, in some cases, AI can perform tasks better than humans. Particularly when it comes to repetitive, detail-oriented tasks like analyzing large numbers of legal documents to ensure relevant fields are filled in properly, AI tools often complete jobs quickly and with relatively few errors. This has helped fuel an explosion in efficiency and opened the door to entirely new business opportunities for some larger enterprises. Prior to the current wave of AI, it would have been hard to imagine using computer software to connect riders to taxis, but today Uber has become one of the largest companies in the world by doing just that. It utilizes sophisticated machine learning algorithms to predict when people are likely to need rides in certain areas, which helps proactively get drivers on the road before they're needed. As another example, Google has become one of the largest players for a range of online services by using machine learning to understand how people use their services and then improving them. In 2017, the company's CEO, Sundar Pichai, pronounced that Google would operate as an "AI first" company. Today's largest and most successful enterprises have used AI to improve their operations and gain advantage on their competitors. What are the advantages and disadvantages of artificial intelligence? Artificial neural networks and deep learning artificial intelligence technologies are quickly evolving, primarily because AI processes large amounts of data much faster and makes predictions more accurately than humanly possible. While the huge volume of data being created on a daily basis would bury a human researcher, AI applications that use machine learning can take that data and quickly turn it into actionable information. As of this writing, the primary disadvantage of using AI is that it is expensive to process the large amounts of data that AI programming requires.

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What is Data Structure?

  • 30/5/2022

  • Mr Rajat Gupta

A data structure is a collection of data values and the relationships between them. Data structures allow programs to store and process data effectively. There are many different data structures, each with its own advantages and disadvantages. Some of the most common data structures are arrays, lists, trees, and graphs. As the name indicates, Data Structure is used for organizing the data in memory. There are various ways of organizing the data in the memory for eg. array, list, stack, queue and many more. The data structure isn’t a programming language like C, C++, Java, etc. It is a set of algorithms that can be used in any programming language to organize the data in the memory. Need of Data Structure As applications are becoming more complex and the amount of data is increasing day by day, which may cause problems with processing speed, searching data, handling multiple requests etc. Data structure provides a way of organizing, managing, and storing data efficiently. With the help of data structure, the data items can be traversed easily. Data structure provides efficiency, reusability and abstraction. It plays an important role in enhancing the performance of a program because the main function of the program is to store and retrieve the user’s data as fast as possible. Why Learn Data Structure? Data structure and algorithms are two of the most important aspects of computer science. Data structures allow us to organize and store data, while algorithms allow us to process that data in a meaningful way. Learning data structure and algorithms will help you become a better programmer. You will be able to write code that is more efficient and more reliable. You will also be able to solve problems more quickly and more effectively.

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