SBCSim

Change management involves a set of changes within entities that poses a risk to the stability of the entity. Similarity index helps to analyze and prioritize the changes, but it provides inaccurate results due to non-consideration of type of similarity. Existing types of similarities also lack accuracy in comparing the versions due to history slicing in case of renaming or shifting. Thus, the proposed combination of fuzzy and hybrid techniques uses modified similarity index that helps in prioritizing the changes in the entities based on the proposed nominal similarity classifications. It reduces the cost of change management by determining risky entities. Results shows that 15% of files, 19% of classes, and 66% of methods pose risk with decrease of 35.29% and 52.53% unstable/risky entities at file and entity level respectively as compared to understand tool. Moreover, MSI captures similarities between entities where SI fails in GIT repositories, thereby enhancing the process of engineering change order.