Name
Abstract | ||
|---|---|---|
Several approaches are currently used in documenting object-oriented application frameworks. Traditional documentation approaches include tutorials, reference manuals, design patterns, cookbooks, and minimalist. The main objective of a framework is to dramatically reduce the time and effort needed in developing complete applications within a family of applications domain. Proper documentation is required in order for a framework to be usable to users, especially to the new users of the framework. This paper discusses and implements the case-based reasoning (CBR) approach to documenting a framework. It is believed that the fastest way to learn is by retrieving previously recorded framework usage experiences or cases. Here, a case is a complete example of how to use a particular component or a set of components within a framework. In CBR, reasoning is based on remembering past cases. Genetic algorithm (GA) is used in implementing the CBR's "retrieve", "reuse", and "revise" steps. During the "revise" and "retain" steps of the CBR, Knuth-Morris-Pratt (KMP) pattern matching algorithm is applied. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/CSIE.2009.456 | CSIE (7) |
Keywords | Field | DocType |
complete example,design pattern,framework usage experience,framework documentation,traditional documentation approach,genetic algorithm,complete application,object-oriented application framework,proper documentation,case-based reasoning,applications domain,case-based reasoning approach,documentation,data mining,case based reasoning,object oriented,gallium,object oriented programming,genetic algorithms,cognition,pattern matching,graphical user interfaces,java,case base reasoning | String searching algorithm,Object-oriented programming,Computer science,Reuse,Software design pattern,Artificial intelligence,Documentation,Case-based reasoning,Pattern matching,Machine learning,Design pattern | Conference |
Citations | PageRank | References |
0 | 0.34 | 8 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hajar Mat Jani | 1 | 2 | 1.47 |
| Lee Sai Peck | 2 | 2 | 0.79 |