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

Millions of people experienced the frustration and failures of the Obamacare website when it first launched. Because the code for the back end is not open source, the exact technicalities of the initial failings are tricky to determine. Many curious programmers and web designers have had time to examine the open source coding on the front end, however, leading to reasonable conclusions about the nature of the overall difficulties.

Lack of End to End Collaboration
The website was developed with multiple contractors for the front-end and back-end functions. The site also needed to be integrated with insurance companies, IRS servers, Homeland Security servers, and the Department of Veterans Affairs, all of whom had their own legacy systems. The large number of parties involved and the complex nature of the various components naturally complicated the testing and integration of each portion of the project.

The errors displayed, and occasionally the lack thereof, indicated an absence of coordination between the parties developing the separate components. A failed sign up attempt, for instance, often resulted in a page that displayed the header but had no content or failure message. A look at end user requests revealed that the database was unavailable. Clearly, the coding for the front end did not include errors for failures on the back end.

Bloat and the Abundance of Minor Issues
Obviously, numerous bugs were also an issue. The system required users to create passwords that included numbers, for example, but failed to disclose that on the form and in subsequent failure messages, leaving users baffled. In another issue, one of the pages intended to ask users to please wait or call instead, but the message and the phone information were accidentally commented out in the code.

While the front-end design has been cleared of blame for the most serious failures, bloat in the code did contribute to the early difficulties users experienced. The site design was heavy with Javascript and CSS files, and it was peppered with small coding errors that became particularly troublesome when users faced bottlenecks in traffic. Frequent typos throughout the code proved to be an additional embarrassment and were another indication of a troubled development process.

NoSQL Database
The NoSQL database is intended to allow for scalability and flexibility in the architecture of projects that will use it. This made NoSQL a logical choice for the health insurance exchange website. The newness of the technology, however, means personnel with expertise can be elusive. Database-related missteps were more likely the result of a lack of experienced administrators than with the technology itself. The choice of the NoSQL database was thus another complication in the development, but did not itself cause the failures.

Another factor of consequence is that the website was built with both agile and waterfall methodology elements. With agile methods for the front end and the waterfall methodology for the back end, streamlining was naturally going to suffer further difficulties. The disparate contractors, varied methods of software development, and an unrealistically short project time line all contributed to the coding failures of the website.

Once again Java tops C as the number one sought after programming language on the internet.  According TIOBE Programming Community Index for February 2013 and five search engines: Google, Bing, Yahoo!, Wikipedia, Amazon, YouTube and Baidu, Java regained its position after being bumped by C in May 2012.

Despite the recent urging by the U.S. Department of Homeland Security of computer users to disable or uninstall Java due to a flaw in Runtime Environment (JRE) 7, Java, has increased its market share of all languages by (+2.03%) in the past six months. The jump in Java’s popularity does not come as a surprise as the Android OS claims massive success in the mobile space.  The top twelve programming languages listed in the index are:

1.  Java
2.  C
3.  Objective-C 
4.  C++
5.  C#
6.  PHP
7.  Python
8.  (Visual) Basic
9.  Perl
10.  Ruby
11. Java Script
12. Visual Basic.NET

Also rising, Python and PHP which are competing to becoming the most popular interpreted language.

Much of success is about performance. It’s about what we do and what we are able to inspire others to do. There are some simple performance principles I have learned in my life, and I want to share them with you.  They really bring success, and what it takes to be successful, into sharp focus. They are also the basis for developing and maintaining an expectation of success.

The Five Principles of Performance

1. We generally get from ourselves and others what we expect. It is a huge fact that you will either live up or down to your own expectations. If you expect to lose, you will. If you expect to be average, you will be average. If you expect to feel bad, you probably will. If you expect to feel great, nothing will slow you down. And what is true for you is true for others. Your expectations for others will become what they deliver and achieve. As Gandhi said, “Be the change you wish to see in the world.”

2. The difference between good and excellent companies is training. The only thing worse than training employees and losing them is to not train them and keep them! A football team would not be very successful if they did not train, practice, and prepare for their opponents. When you think of training as practice and preparation, it makes you wonder how businesses survive that do not make significant training investments in their people.

Actually, companies that do not train their people and invest in their ability don’t last. They operate from a competitive disadvantage and are eventually gobbled up and defeated in the marketplace. If you want to improve and move from good to excellent, a good training strategy will be the key to success.