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Current Result Document :
ÇѱÛÁ¦¸ñ(Korean Title) |
Ŭ·¡½º Ư¼º ±â°èÇнÀ¿¡ ±â¹ÝÇÑ Å¬·¡½º À̸§ÀÇ Á¢¹Ì»ç °ËÁõ ±â¹ý |
¿µ¹®Á¦¸ñ(English Title) |
Validation Technique for Class Name Postfixes Based on the Machine Learning of Class Properties |
ÀúÀÚ(Author) |
ÀÌÈ«¼®
ÀÌÁØÇÏ
ÀÌÀÏ·Î
¹Ú¼öÁø
¹Ú¼ö¿ë
Hongseok Lee
Junha Lee
Illo Lee
Soojin Park
Sooyong Park
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¿ø¹®¼ö·Ïó(Citation) |
VOL 04 NO. 06 PP. 0247 ~ 0252 (2015. 06) |
Çѱ۳»¿ë (Korean Abstract) |
¼ÒÇÁÆ®¿þ¾îÀÇ ±Ô¸ð°¡ Ä¿Áö°í º¹À⼺ÀÌ Áõ°¡ÇÔ¿¡ µû¶ó ¼ÒÇÁÆ®¿þ¾îÀÇ À¯Áöº¸¼ö°¡ º¸´Ù Áß¿äÇØÁö°í ÀÖÀ¸¸ç À¯Áöº¸¼ö¼º¿¡ ¸¹Àº ¿µÇâÀ» ¹ÌÄ¡´Â ¿äÀÎ Áß Çϳª´Â ¼Ò½ºÄÚµå °¡µ¶¼ºÀÌ´Ù. °¡µ¶¼ºÀÇ 90% ÀÌ»ó ¿µÇâÀ» ³¢Ä¡´Â ¿äÀÎÀº ¼Ò½ºÄڵ忡¼ »ç¿ëµÇ´Â ½Äº°ÀÚµéÀÇ À̸§À̸ç À̸¦ À§ÇÑ ±âÁ¸ ¿¬±¸µé¿¡¼´Â Ŭ·¡½ºÀÇ ½Äº°ÀÚ·Î »ç¿ëµÈ ¾îÈÖ¸¦ ÀÌ¿ëÇÏ¿© ½Äº°ÀÚÀÇ À̸§À» °ËÁõÇÑ´Ù. ÇÏÁö¸¸ ´ëºÎºÐÀÇ °ü·Ã ¿¬±¸´Â ±× Ư¼º»ó °³Ã¼ÀÇ µµ¸ÞÀÎ °ü·Ã Ư¼º¸¸À» °í·ÁÇÏ°Ô µÇ¸ç Ŭ·¡½º ³»ÀÇ ¾îÈÖ°¡ ÀûÀýÇÏÁö ¸øÇÑ °æ¿ì Àû¿ëÇÒ ¼ö ÀÖ´Â ¹üÀ§°¡ ÇÑÁ¤ÀûÀ̶ó´Â ÇÑ°èÁ¡ÀÌ ÀÖ´Ù. º» ³í¹®¿¡¼´Â Ŭ·¡½ºÀÇ Æ¯¼ºÀ» ÃßÃâÇÏ¿© ÀÇ»ç°áÁ¤Æ®¸® ±â¹ýÀ» ÅëÇØ ±â°èÇнÀÀ» ½ÃŲ ÈÄ Å¬·¡½º ¿ªÇÒ ¸ðµ¨À» »ý¼ºÇϸç À̸¦ ÀÌ¿ëÇÏ¿© À̸§À» °ËÁõÇÒ ´ë»ó Ŭ·¡½ºÀÇ ¿ªÇÒ¿¡ ÇØ´çÇÏ´Â Á¢¹Ì»ç¸¦ ÃßõÇÏ°Ô µÇ¾î Ŭ·¡½º À̸§ °ËÁõ º¸°í¼¸¦ »ý¼ºÇÑ´Ù. º» ¿¬±¸ ±â¹ýÀÇ È¿¿ë¼ºÀ» °ËÁõÇϱâ À§ÇØ 4°³ÀÇ ¿ÀǼҽº ÇÁ·ÎÁ§Æ®¿¡ ´ëÇÏ¿© º» ¿¬±¸ ±â¹ýÀ» Àû¿ëÇÏ¿´°í Ŭ·¡½º ¿ªÇÒ Á¤º¸¸¦ ´ã°í ÀÖ´Â 5°³ÀÇ Á¢¹Ì»ç¿¡ ´ëÇØ Á¤È®µµ¿Í ÀçÇöÀ², ROC °î¼±°ú °°Àº ÁöÇ¥¸¦ Á¦½ÃÇÏ¿´´Ù. |
¿µ¹®³»¿ë (English Abstract) |
As software has gotten bigger in magnitude and the complexity of software has been increased, the maintenance has gained in-creasing attention for its significant impact on the cost. Identifiers have an impact on more than 90 percent of the readability which accounts for a majority portion of the maintenance activities. For this reason, the existing works focus on domain-specific features based on identifiers. However, their approaches have a limitation when either a class name does not reflect the intention of its context or a class naming is incorrect. Therefore, this paper suggests a series of class name validation process by extracting properties of classes, building learning model by applying a decision tree technique of machine learning, and generating a validation report containing the list of recommendable postfixes of classes to be validated. To evaluate this, four open source projects are selected and indicators such as precision, recall, and ROC curve present the value of this work when it comes to five specific postfixes including functional information on class names.
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Å°¿öµå(Keyword) |
¼ÒÇÁÆ®¿þ¾î À¯Áöº¸¼ö
°¡µ¶¼º
Ŭ·¡½º À̸§
±â°èÇнÀ
Software Maintenance
Readability
Class Name
Machine Learning
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