We’re often asked by companies about how they can get the most value from Agile/Scrum practices. More specifically, they want to know if they are being as effective as best they possibly can be by using the Scrum framework for their explicit needs.

The other objective for individuals is determining if it necessary to be certified in order to be effective in the Agile Scrum world?   In short, a good Scrum Master must understand four things: the business they work in, the technology they work with, the Agile and Scrum principles, and, most importantly, people!  Based on these facts, Scrum Master Certification is not enough – real life experience and a bit of soft skills should be part and parcel of their training. For organizations, the main goal is to understand industry best practices when adopting and applying agile principles, to build strong teams, understand and distill business needs into software requirements.

In terms of getting a good grip on training for Agile/Scrum, one can opt to pursue a certification in Scrum (CSM) Certified Scrum Master for personal reasons or for a job requirement. Or, one can simply opt to learn the benefits and pitfalls of the methodology and decide the best approach for them.

There are different ways to get started with Agile training. Below are two of the most common paths to Agile our students take.

A business rule is the basic unit of rule processing in a Business Rule Management System (BRMS) and, as such, requires a fundamental understanding. Rules consist of a set of actions and a set of conditions whereby actions are the consequences of each condition statement being satisfied or true. With rare exception, conditions test the property values of objects taken from an object model which itself is gleaned from a Data Dictionary and UML diagrams. See my article on Data Dictionaries for a better understanding on this subject matter.

A simple rule takes the form:

if condition(s)

then actions.

An alternative form includes an else statement where alternate actions are executed in the event that the conditions in the if statement are not satisfied:

if condition(s)

then actions

else alternate_actions

It is not considered a best prectice to write rules via nested if-then-else statements as they tend to be difficult to understand, hard to maintain and even harder to extend as the depth of these statements increases; in other words, adding if statements within a then clause makes it especially hard to determine which if statement was executed when looking at a bucket of rules. Moreoever, how can we determine whether the if or the else statement was satisfied without having to read the rule itself. Rules such as these are often organized into simple rule statements and provided with a name so that when reviewing rule execution logs one can determine which rule fired and not worry about whether the if or else statement was satisfied. Another limitation of this type of rule processing is that it does not take full advantage of rule inferencing and may have a negative performance impact on the Rete engine execution. Take a class with HSG and find out why.

Rule Conditions

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.

Related:

 What Are The 10 Most Famous Software Programs Written in Python?

Python, a Zen Poem