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 */

Globalization
Globalization is the fundamental force changing IT service delivery and business's competitive activities in almost every vertical market — and thus economies — in some way, shape or form. One might say that globalization is not a new trend and has been commonplace for quite some time now. Yes, but with the changing economic environment globalizations has special implications for the IT outsourcing industry. With developed countries like the U.S. keeping a strict eye on generating local jobs, IT outsourcing especially in Asian countries such as India and China is expected to see globalization brining in big shifts in business strategy

Potential Impact of Globalization

·         Increase in near shoring in addition to outsourcing. Near shoring essentially refers to existing IT companies setting up development/delivery centers in Nordic and South American regions in order to offer same time zone services and also bypass the laws governing local hiring

·         A truly global delivery model. Service delivery models will have to become more efficient and flexible and work well even if service teams spread across continents

This will mean that large IT outsourcing companies such as TCS will have to expand their presence globally from just having sales offices to actual delivery teams shipping out solutions.

Studying a functional programming language is a good way to discover new approaches to problems and different ways of thinking. Although functional programming has much in common with logic and imperative programming, it uses unique abstractions and a different toolset for solving problems. Likewise, many current mainstream languages are beginning to pick up and integrate various techniques and features from functional programming.

Many authorities feel that Haskell is a great introductory language for learning functional programming. However, there are various other possibilities, including Scheme, F#, Scala, Clojure, Erlang and others.

Haskell is widely recognized as a beautiful, concise and high-performing programming language. It is statically typed and supports various cool features that augment language expressivity, including currying and pattern matching. In addition to monads, the language support a type-class system based on methods; this enables higher encapsulation and abstraction. Advanced Haskell will require learning about combinators, lambda calculus and category theory. Haskell allows programmers to create extremely elegant solutions.

Scheme is another good learning language -- it has an extensive history in academia and a vast body of instructional documents. Based on the oldest functional language -- Lisp -- Scheme is actually very small and elegant. Studying Scheme will allow the programmer to master iteration and recursion, lambda functions and first-class functions, closures, and bottom-up design.

Supported by Microsoft and growing in popularity, F# is a multi-paradigm, functional-first programming language that derives from ML and incorporates features from numerous languages, including OCaml, Scala, Haskell and Erlang. F# is described as a functional language that also supports object-oriented and imperative techniques. It is a .NET family member. F# allows the programmer to create succinct, type-safe, expressive and efficient solutions. It excels at parallel I/O and parallel CPU programming, data-oriented programming, and algorithmic development.

Scala is a general-purpose programming and scripting language that is both functional and object-oriented. It has strong static types and supports numerous functional language techniques such as pattern matching, lazy evaluation, currying, algebraic types, immutability and tail recursion. Scala -- from "scalable language" -- enables coders to write extremely concise source code. The code is compiled into Java bytecode and executes on the ubiquitous JVM (Java virtual machine).

Like Scala, Clojure also runs on the Java virtual machine. Because it is based on Lisp, it treats code like data and supports macros. Clojure's immutability features and time-progression constructs enable the creation of robust multithreaded programs.

Erlang is a highly concurrent language and runtime. Initially created by Ericsson to enable real-time, fault-tolerant, distributed applications, Erlang code can be altered without halting the system. The language has a functional subset with single assignment, dynamic typing, and eager evaluation. Erlang has powerful explicit support for concurrent processes.

Computer Programming as a Career?

What little habits make you a better software engineer?

Python programming language is general purpose open source programming language. One of its main features is flexibility and ease of use. Python has a variety of useful set of utilities and libraries for data processing and analytical tasks. Currently due to the rise in demand of big data processing python has grown in popularity because its features are easy to use which are core to the processing of huge chunks of information.

Guido Van Rossum, the pioneer of python, introduced python in the year 1980 and then implemented it in 1989. The intention behind the development of python was to make it open source language that can also be used for commercial projects. The fundamental principle of python is to write the code that is easy to use, highly readable and embrace writing fewer lines of code for achieving a particular task. One of the most popular standard libraries which have ready to use tools for performing a various work is Python Package Index. It was introduced in January 2016 and contains more than 72,000 packages for third-party software usage.

Python plays a critical role in linking data to customers. Recently python has found few entry barriers and many people have had access to have experienced the power of python in the past. So, what makes python the best language for big data analytics?

One of the reasons to choose python is that python ecosystem is very vibrant, the ratings at Redmonk are a proof of the strength python community. The Redmonk ranking is based on StackOverflow discussions and contribution made in Github to determine the popularity of programming language on the method used by users to ask questions about Python and the number of the open source projects contributions.