I will begin our blog on Java Tutorial with an incredibly important aspect of java development:  memory management.  The importance of this topic should not be minimized as an application's performance and footprint size are at stake.

From the outset, the Java Virtual Machine (JVM) manages memory via a mechanism known as Garbage Collection (GC).  The Garbage collector

• Manages the heap memory.   All obects are stored on the heap; therefore, all objects are managed.  The keyword, new, allocates the requisite memory to instantiate an object and places the newly allocated memory on the heap.  This object is marked as live until it is no longer being reference.
• Deallocates or reclaims those objects that are no longer being referened. 
• Traditionally, employs a Mark and Sweep algorithm.  In the mark phase, the collector identifies which objects are still alive.  The sweep phase identifies objects that are no longer alive.
• Deallocates the memory of objects that are not marked as live.
• Is automatically run by the JVM and not explicitely called by the Java developer.  Unlike languages such as C++, the Java developer has no explict control over memory management.
• Does not manage the stack.  Local primitive types and local object references are not managed by the GC.

So if the Java developer has no control over memory management, why even worry about the GC?  It turns out that memory management is an integral part of an application's performance, all things being equal.  The more memory that is required for the application to run, the greater the likelihood that computational efficiency suffers. To that end, the developer has to take into account the amount of memory being allocated when writing code.  This translates into the amount of heap memory being consumed.

Memory is split into two types:  stack and heap.  Stack memory is memory set aside for a thread of execution e.g. a function.  When a function is called, a block of memory is reserved for those variables local to the function, provided that they are either a type of Java primitive or an object reference.  Upon runtime completion of the function call, the reserved memory block is now available for the next thread of execution.  Heap memory, on the otherhand, is dynamically allocated.  That is, there is no set pattern for allocating or deallocating this memory.  Therefore, keeping track or managing this type of memory is a complicated process. In Java, such memory is allocated when instantiating an object:

String s = new String();  // new operator being employed
String m = "A String";    /* object instantiated by the JVM and then being set to a value.  The JVM
calls the new operator */

Technology has continued to evolve in ways that few would have been able to imagine. This has allowed electronics to become smarter, more connected and far more useful.

With the Internet of Things (IoT), they're allowing more than just computers to become connected to the Internet. This aims to make the life of the average person easier, better and more care-free.

Let's examine why the Internet of Things has become such a powerful idea that an estimated one out of every five developers currently works on an IoT project.


What is the Internet of Things?

The Internet of Things hinges on one seemingly simple concept: electronics can be embedded in machines, clothing, animals and even people to provide a networked world where the whole is more than just the sum of its parts.

For example, consider how the Internet of Things can influence things like refrigerators. They can be networked directly to the manufacturer for readings that can warn if the refrigerator is about to malfunction. They can even be connected to a grocery shopping service to allow someone to restock them automatically or to notify the owner that the refrigerator is almost out of an item.

The most interesting notion about the Internet of Things is that it's not just a situation where one “thing” connects with a party. They typically communicate with other things, which in turn allows for a network of automated processes to occur.

These processes can simplify and expedite tedious tasks to make everyday life for everyone easier, which is why projects involving the Internet of Things are so popular.


How Prevalent is IoT Development?

An estimated one in five developers are currently developing projects for the Internet of Things. Their chosen languages vary widely because of the flexibility that IoT enjoys.

For example, IoT projects that hinge on interacting with mobile phones tend to have apps written in JavaScript or Java. The back-end code that runs the IoT functionality for machines tends to be written in Assembly, C++,Java,Perl,Pythonor another compiled language for efficiency.

To put the growth of IoT work into perspective, Evans Data Corp. performed research to create predictions about IoT projects in 2014. They stated that 17% of companies would be developing IoT projects.

In this year, that figure's risen to a solid 19%. Given the fact that 44% of developers have stated that they will enter into the IoT scene this year or next, this means that development will only grow in the coming future.


The Future Involving the Internet of Things

Development of IoT-related projects will likely explode in the next few years. The advantages it brings, such as more efficient work in manufacturing environments and the projected 15% savings to the restaurant industry over the next five years, will make it one of the most valuable technological changes in the near future.

Without a comprehensive understanding of the Internet of Things and the skills to lead IoT projects, businesses and developers may find themselves falling behind. Don't let the Internet of Things pass you by.

The interpreted programming language Python has surged in popularity in recent years. Long beloved by system administrators and others who had good use for the way it made routine tasks easy to automate, it has gained traction in other sectors as well. In particular, it has become one of the most-used tools in the discipline of numerical computing and analysis. Being put to use for such heavy lifting has endowed the language with a great selection of powerful libraries and other tools that make it even more flexible. One upshot of this development has been that sophisticated business analysts have also come to see the language as a valuable tool for those own data analysis needs.

Greatly appreciated for its simplicity and elegance of syntax, Python makes an excellent first programming language for previously non-technical people. Many business analysts, in fact, have had success growing their skill sets in this way thanks to the language's tractability. Long beloved by specialized data scientists, the iPython interactive computing environment has also attracted great attention within the business analyst’s community. Its instant feedback and visualization options have made it easy for many analysts to become skilled Python programmers while doing valuable work along the way.

Using iPython and appropriate notebooks for it, for example, business analysts can easily make interactive use of such tools as cohort analysis and pivot tables. iPython makes it easy to benefit from real-time, interactive researches which produce immediately visible results, including charts and graphs suitable for use in other contexts. Through becoming familiar with this powerful interactive application, business analysts are also exposing themselves in a natural and productive way to the Python programming language itself.

Gaining proficiency with this language opens up further possibilities. While interactive analytic techniques are of great use to many business analysts, being able to create fully functioning, independent programs is of similar value. Becoming comfortable with Python allows analysts to tackle and plumb even larger data sets than would be possible through an interactive approach, as results can be allowed to accumulate over hours and days of processing time.

This ability can sometime allow business analysts to address the so-called "Big Data" questions that can otherwise seem the sole province of specialized data scientists. More important than this higher level of independence, perhaps, is the fact that this increased facility with data analysis and handling allows analysts to communicate more effectively with such stakeholders. Through learning a programming language which allows them to begin making independent inroads into such areas, business analysts gain a better perspective on these specialized domains, and this allows them to function as even more effective intermediaries.

Related:

Who Are the Main Players in Big Data?

If you're someone who's interested in computer programming, chances are you've considered pursuing a career in it. However, being a computer programmer is definitely not for everyone, as it takes some special characteristics to succeed as a computer programmer.

Good at Math

While you don't have to be a math genius in order to be a good computer programmer, being good at math really does help. In general, as long as you know your trigonometry and advanced high school algebra, you should be set for programming.

However, in a few instances, knowledge of more advanced math ends up being necessary. For example, for shader programming, you should be familiar with integration of multiple variables, matrix algebra, and basic differentiation. You will also require considerable math skills in order to program 3D.

Excellent Problem Solver

To be a successful computer programmer, you definitely need to be an excellent problem solver. It is vital for a computer programmer to break a problem down into small parts. They must then be able to decide the best way to approach individual pieces of the problem. Computer programmers also need to know how to anticipate and prevent potential problems. While problem-solving, they also need to keep in mind things like user experience and performance.

If you're not a good problem solver, knowing a particular language and syntax will be useless if you can't even identify the problem at hand. Therefore, excellent problem solving skills are a critical foundation for computer programming.

Patience

If you are not a patient person, you will quickly become very frustrated with computer programming. Problem-solving is not always easy and fast. In fact, it may take a very long time, especially if you're either inexperienced or working on an especially hard project.

Debugging after the coding process is also very frustrating and tedious. No matter how hard you try, you will always have bugs in your coding, and these bugs, while often easy to fix, tend to be very difficult to detect. Therefore, you will end up spending a lot of your time searching for bugs that take very little time to fix.

Well-Rounded Skills

Generally, computer programmers who are very skilled in one area tend to stick around longer than jack-of-all-trades, as specialized programmers are harder to replace with outsourcing than general programmers. Therefore, it will do you well to specialize in one area of computer programming.

However, while specializing is good, you should still know at least a little about everything, especially skills that relate to the area you specialize in. For example, if you're a core Java programmer, you should know about SQL programming and ideally a scripting language or some regular expressions.

As you can see, not everyone has what it takes to pursue computer programming as a career and succeed at it. In fact, just because you love to program doesn't mean it's a good career choice for you. However, if you feel that you possess all the characteristics listed above, then you should definitely consider computer programming as a career.