Title :
Recognizing Sorting Algorithms with the C4.5 Decision Tree Classifier
Author :
Taherkhani, Ahmad
Author_Institution :
Sch. of Sci. & Technol., Dept. of Comput. Sci. & Eng., Aalto Univ., Aalto, Finland
fDate :
June 30 2010-July 2 2010
Abstract :
We present a method for automatic algorithm recognition, which consists of two phases. First, the target algorithms are converted into characteristic vectors, which are computed based on static analysis of program code including various statistics of language constructs and analysis of Roles of Variables. In the second phase, the algorithms are classified based on these vectors using the C4.5 decision tree classifier. We have developed a prototype and successfully applied the method to sorting algorithms. Evaluated with leave-one-out technique, the accuracy of the constructed decision tree classifier is 97.1%.
Keywords :
decision trees; pattern classification; sorting; statistical analysis; C4.5 decision tree classifier; algorithm recognition; language constructs statistics; leave-one-out technique; program code analysis; roles-of-variables analysis; sorting algorithms; Algorithm design and analysis; Classification tree analysis; Computational complexity; Computer languages; Computer science; Decision trees; Programming profession; Prototypes; Sorting; Statistical analysis; Algorithm recognition; C4.5 algorithm; program comprehension; program understanding; roles of variables;
Conference_Titel :
Program Comprehension (ICPC), 2010 IEEE 18th International Conference on
Conference_Location :
Braga, Minho
Print_ISBN :
978-1-4244-7604-6
Electronic_ISBN :
1092-8138
DOI :
10.1109/ICPC.2010.11