{"id":167744,"date":"2014-11-25T00:00:00","date_gmt":"2014-11-25T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/the-uniqueness-of-changes-characteristics-and-applications\/"},"modified":"2020-01-10T09:59:20","modified_gmt":"2020-01-10T17:59:20","slug":"the-uniqueness-of-changes-characteristics-and-applications","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/the-uniqueness-of-changes-characteristics-and-applications\/","title":{"rendered":"The Uniqueness of Changes: Characteristics and Applications"},"content":{"rendered":"<div class=\"asset-content\">\n<p>Changes in software development come in many forms. Some<br \/>\nchanges are frequent, idiomatic, or repetitive (e.g. adding checks for nulls or<br \/>\nlogging important values) while others are unique. We hypothesize that<br \/>\nunique changes are different from the more common similar (or non-unique)<br \/>\nchanges in important ways; they may require more expertise or represent code<br \/>\nthat is more complex or prone to mistakes. As such, these changes are worthy of<br \/>\nstudy. In this paper, we present a definition of unique changes and provide a<br \/>\nmethod for identifying them in software project history. Based on the results<br \/>\nof applying our technique on the Linux kernel and two large projects at<br \/>\nMicrosoft, we present an empirical study of unique changes. We explore how<br \/>\nprevalent unique changes are and characterize where they occur along the<br \/>\narchitecture of the project. We further investigate developers&#8217; contribution<br \/>\ntowards uniqueness of changes. We also describe potential applications of<br \/>\nleveraging the uniqueness of change and implement two such applications,<br \/>\nevaluating the risk of changes based on uniqueness and providing change<br \/>\nrecommendations for non-unique changes.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Changes in software development come in many forms. Some changes are frequent, idiomatic, or repetitive (e.g. adding checks for nulls or logging important values) while others are unique. We hypothesize that unique changes are different from the more common similar (or non-unique) changes in important ways; they may require more expertise or represent code that 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