Abstract
Software systems changes constantly with time. Changing the software affects all the classes associated with it. For effective project management it becomes important to predict change impact classes in earlier phases of software life cycle. This paper aims to develop a novel model using dynamic metrics and several behavioural dependencies. Using code analyser trace events 30 different metrics are analysed which are further used for refining the degree of change impact feature of a class. Further the model is validated using K-means clustering technique, naïve Bayes classification and logistic regression in WEKA tool. Validation of the model is done using open source software Art of Illusion (AoI).
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Project Organisation and Management
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
