Applications are becoming more and more sophisticated as languages such as Python open the doors to the world of programming for people who have the creative vision but always felt actually writing code was beyond their grasp.

A large part of any programs success is based on how well it can react to the events which it has been programmed to understand and listen for.

A good example of an event would be when the user clicks a button on the applications window. What happens when that button is clicked?

Well, the first thing that happens is the operating system sends out a message to let any listening software know that the button was clicked. Next, your application needs to do something in response to that event.

We are not all equally motivated. Some people have more self-drive than other people. This is why we find that some people always end up at the top even when the odds are against them. An employee, with this realization, through the Human Resource department, should be able to design efficient career development systems. For this system to work, the employer must understand the nature of the business environment in which they are operating.

Why Train Employees?

The purpose of training employees is to enable them to grow with time and increase their efficiency. The business world is quite dynamic, nothing stays the same for long. Training one’s employees allows them to keep abreast with the ever changing technological advancements and many other factors that are relevant to his/her line of work. Employees cannot be expected to solve all their employer’s expectations with static skills and techniques. Even the most updated technology becomes obsolete at some point.
People are the biggest assets in organizations. For an establishment to flourish, it is important that the employer understands certain key things that help spur their development.

In a report from the Harvard Business Review, “The Impact of Employee Engagement of Performance,” the most impactful employee drivers are:

No industry is as global as software development.  Pervasive networking means that software developers can, and do, work from anywhere. This has led many businesses to hiring development subcontractors in other countries, aiming to find good development talent at lower prices, or with fewer hassles on entry into the US.

While this is an ongoing and dynamic equilibrium, there are compelling reasons for doing software development in the United States, or using a hybrid model where some parts of the task are parceled out to foreign contractors and some are handled locally.

Development Methodologies

The primary reason for developing software overseas is cost reduction. The primary argument against overseas software development is slower development cycles. When software still used the "waterfall" industrial process for project management (where everything is budgeted in terms of time at the beginning of the project), offshoring was quite compelling. As more companies emulate Google and Facebook's process of "release early, update often, and refine from user feedback," an increasing premium has been put on software teams that are small enough to be agile (indeed, the development process is called Agile Development), and centralized enough, in terms of time zones, that collaborators can work together. This has made both Google and Facebook leaders in US-based software development, though they both still maintain teams of developers in other countries tasked with specific projects.

Localization For Americans

The United States is still one of the major markets for software development, and projects aimed at American customers needs to meet cultural norms. This applies to any country, not just the U.S. This puts a premium on software developers who aren't just fluent in English, but native speakers, and who understand American culture. While it's possible (and even likely) to make server-side software, and management utilities that can get by with terse, fractured English, anything that's enterprise-facing or consumer-facing requires more work on polish and presentation than is practical using outsourced developers. There is a reason why the leaders in software User Interface development are all US-based companies, and that's because consumer-focused design is still an overwhelming US advantage.

Ongoing Concerns

The primary concern for American software development is talent production. The US secondary education system produces a much smaller percentage of students with a solid math and engineering background, and while US universities lead the world in their computer science and engineering curricula, slightly under half of all of those graduates are from foreign countries, because American students don't take the course loads needed to succeed in them. Software development companies in the United States are deeply concerned about getting enough engineers and programmers out of the US university system. Some, such as Google, are trying to get programmers hooked on logical problem solving at a young age, with the Summer of Code programs. Others, like Microsoft, offer scholarships for computer science degrees.

Overall, the changes in project management methodologies mean that the US is the current leader in software development, and so long as the primary market for software remains English and American-centric, that's going to remain true. That trend is far from guaranteed, and in the world of software, things can change quickly.

Writing Python in Java syntax is possible with a semi-automatic tool. Programming code translation tools pick up about 75% of dynamically typed language. Conversion of Python to a statically typed language like Java requires some manual translation. The modern Java IDE can be used to infer local variable type definitions for each class attribute and local variable.


Translation of Syntax
Both Python and Java are OO imperative languages with sizable syntax constructs. Python is larger, and more competent for functional programming concepts. Using the source translator tool, parsing of the original Python source language will allow for construction of an Abstract Source Tree (AST), followed by conversion of the AST to Java.

Python will parse itself. This capability is exhibited in the ast module, which includes skeleton classes. The latter can be expanded to parse and source each node of an AST. Extension of the ast.NodeVisitor class enables python syntax constructs to be customized using translate.py and parser.py coding structure.

The Concrete Syntax Tree (CST) for Java is based on visit to the AST. Java string templates can be output at AST nodes with visitor.py code. Comment blocks are not retained by the Python ast Parser. Conversion of Python to multi-line string constructs with the translator reduces time to script.


Scripting Python Type Inference in Java
Programmers using Python source know that the language does not contain type information. The fact that Python is a dynamic type language means object type is determined at run time. Python is also not enforced at compile time, as the source is not specified. Runtime type information of an object can be determined by inspecting the __class__.__name__ attribute.

Python’s inspect module is used for constructing profilers and debugging.
Implementation of def traceit (frame, event, arg) method in Python, and connecting it to the interpreter with sys.settrace (traceit) allows for integration of multiple events during application runtime.

Method call events prompt inspect and indexing of runtime type. Inspection of all method arguments can be conducted. By running the application profiler and exercising the code, captured trace files for each source file can be modified with the translator. Generating method syntax can be done with the translator by search and addition of type information. Results in set or returned variables disseminate the dynamic code in static taxonomy.

The final step in the Python to Java scrip integration is to administer unsupported concepts such as value object creation. There is also the task of porting library client code, for reproduction in Java equivalents. Java API stubs can be created to account for Python APIs. Once converted to Java the final clean-up of the script is far easier.

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