Title :
Predicting Code Change by Using Static Metrics
Author :
Mauczka, Andreas ; Grechenig, Thomas ; Bernhart, Mario
Author_Institution :
Reasearch Group for Ind. Software, Vienna Univ. of Technol., Vienna, Austria
Abstract :
Maintenance of software is risky, potentially expensive - and inevitable. The main objective of this study is to examine the relationship of code change, referred to as maintenance effort, with source-level software metrics. This approach varies from the typical approach of evaluating software metrics against failure data and provides a different angle on the validation of software metrics. The goal of this study is to show through exhaustive data mining that a relation between software metrics and code change exists. Once this connection is established, a set of software metrics is identified, which will be used in further studies to predict code change in problematic modules identified by the software metrics at an early development stage.
Keywords :
data mining; software maintenance; software metrics; code change prediction; data mining; maintenance effort; software maintenance; source-level software metrics; static metrics; Conference management; History; Java; Packaging; Regression analysis; Risk management; Software engineering; Software metrics; Statistical analysis; Technology management; Change Data; Software Metrics; Validation;
Conference_Titel :
Software Engineering Research, Management and Applications, 2009. SERA '09. 7th ACIS International Conference on
Conference_Location :
Haikou
Print_ISBN :
978-0-7695-3903-4
DOI :
10.1109/SERA.2009.30