Introduction to Class-Responsibility-Collaborator (CRC) Modeling

Class-responsibility-collaborator (CRC) modeling is a means to identify and organize classes relevant to system requirements. CRC model is a collection of index cards and it consists of three parts:

Classes : It is a collection of similar objects.
- Entity classes or business classes are obtained directly from statement of the problem. The information contained in these classes are important to users but they do not display themselves.
- Boundary classes are used to create interface which user sees and interacts with as software is used.
- Controller classes are designed to manage creation or update of entity objects, instantiation of boundary objects, communication between objects and validation of data.

Responsibility : something that a class knows or does. Some guidelines that can be applied for allocating responsibilities to classes are:
- System intelligence should be distributed across classes to best address the needs of the problem.
- Each responsibility should be stated as generally as possible.
- Information and the behavior related to it should reside within the same class.
- Information about one thing should be localized with a single class not distributed across multiple classes.
- Responsibilities should be shared among related classes when appropriate.

Collaborator : another class that the class interacts with to fulfill the responsibilities.
- It takes one of two forms : a request for information or a request to do something.
- If a class cannot fulfill all of its obligations itself, then a collaboration is required.
- Collaboration identifies relationship between classes.

Error Detection Methods Cont...

- Cyclic Redundancy Check (CRC) :
This error detection method computes the remainder of a polynomial division of a generator polynomial into a message. The remainder, which is usually 16 or 32 bits, is then appended to the message. When another remainder is computed, a non-zero value indicates an error. Depending on the generator polynomial's size, the process can fail in several ways, however, it is very difficult to determine how effective a given CRC will be at detecting errors. The probability that a random code word is valid (not detectable as an error), is completely a function of the code rate: 1 - 2-(n - k). Where n is the number of bits of formed from k original bits of data ,(n - k) is the number of redundant bits, r.
Use of the CRC technique for error correction normally requires the ability to send retransmission requests back to the data source.

- Hamming distance based checks :
If we want to detect d bit errors in an n bit word we can map every n bit word into a bigger n+d+1 bit word so that the minimum Hamming distance between each valid mapping is d+1. This way, if one receives a n+d+1 word that doesn't match any word in the mapping (with a Hamming distance x <= d+1 from any word in the mapping) it can successfully detect it as an erroneous word. Even more, d or fewer errors will never transform a valid word into another, because the Hamming distance between each valid word is at least d+1, and such errors only lead to invalid words that are detected correctly. Given a stream of m*n bits, we can detect x <= d bit errors successfully using the above method on every n bit word. In fact, we can detect a maximum of m*d errors if every n word is transmitted with maximum d errors.