HP is taking legal action against Oracle for allegedly breaching its 2010 partnership agreement of porting HP’s core software products with the latest versions of Itanium. In March, Oracle announced it would not be developing any new versions for products designed for the Itanium processor. Itanium has the ability to power the so-called Business Critical Systems hardware for extremely demanding enterprise applications. However, Oracle said the chip line is about to die.

The companies’ lawyer met in the Santa Clara County Superior Court with Judge James Kleinberg presiding to discuss their side of the event. Others in the courtroom included Ann Livermore, HP board member and former enterprise business chief, and Oracle’s co-President Safra Catz. Catz and Livermore were the two key negotiators for the agreement. Livermore was to testify later in the day. Kleinberg is set to rule if the companies had a legally binding contract.

Jeff Thomas, HP’s lawyer, focused on the so-called Hurd Agreement wording, where the companies reiterated their partnership after Oracle hired Mark Hurd, former CEO for HP. HP also sued Hurd for breaking the confidentiality agreement.

Thomas and the lead lawyer for Oracle focused on one paragraph of the agreement, which read Oracle would continue to provide its product suite on the HP platform in a way that’s consistent with the existing partnership before Hurd’s hiring.

The iconic software company that is based in King County Washington has been getting almost universally slammed from it's recent Los Angeles press announcement about its entry into the hardware business with the convertible laptop/tablet known as Surface.

Certainly I can see the point that it is now competing with its hardware vendors/partners. Intel has done a good job in the arena creating 'reference designs' without competing with its partners.

There is another viewpoint which seems to be ignored. The cold facts are Microsoft is a public company. This puts Microsoft in a legal position of doing the most it can to return value to its shareholders. Failure to do so means somebody is going to jail.

Microsoft has a vision, which at the end of the day is, a certain way to get enough people to see enough value to hand over their money, to fulfill their fiduciary duty.

Java still has its place in the world of software development, but is it quickly becoming obsolete by the more dynamically enabled Python programming language? The issue is hotly contested by both sides of the debate. Java experts point out that Java is still being developed with more programmer friendly updates. Python users swear that Java can take up to ten times longer to develop. Managers that need to make the best decision for a company need concrete information so that an informed and rational decision can be made.

First, Java is a static typed language while Python is dynamically typed. Static typed languages require that each variable name must be tied to both a type and an object. Dynamically typed languages only require that a variable name only gets bound to an object. Immediately, this puts Python ahead of the game in terms of productivity since a static typed language requires several elements and can make errors in coding more likely.

Python uses a concise language while Java uses verbose language. Concise language, as the name suggests, gets straight to the point without extra words. Removing additional syntax can greatly reduce the amount of time required to program.  A simple call in Java, such as the ever notorious "Hello, World" requires three several lines of coding while Python requires a single sentence. Java requires the use of checked exceptions. If the exceptions are not caught or thrown out then the code fails to compile. In terms of language, Python certainly has surpassed Java in terms of brevity.

Additionally, while Java's string handling capabilities have improved they haven't yet matched the sophistication of Python's. Web applications rely upon fast load times and extraneous code can increase user wait time. Python optimizes code in ways that Java doesn't, and this can make Python a more efficient language. However, Java does run faster than Python and this can be a significant advantage for programmers using Java. When you factor in the need for a compiler for Java applications the speed factor cancels itself out leaving Python and Java at an impasse.

While a programmer will continue to argue for the language that makes it easiest based on the programmer's current level of knowledge, new software compiled with Python takes less time and provides a simplified coding language that reduces the chance for errors. When things go right, Java works well and there are no problems. However, when errors get introduced into the code, it can become extremely time consuming to locate and correct those errors. Python generally uses less code to begin with and makes it easier and more efficient to work with.

Ultimately, both languages have their own strengths and weaknesses. For creating simple applications, Python provides a simpler and more effective application. Larger applications can benefit from Java and the verbosity of the code actually makes it more compatible with future versions. Python code has been known to break with new releases. Ultimately, Python works best as a type of connecting language to conduct quick and dirty work that would be too intensive when using Java alone. In this sense, Java is a low-level implementation language. While both languages are continuing to develop, it's unlikely that one language will surpass the other for all programming needs in the near future.

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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