The Grizzly, February 15, 2007

Darfur Fast Week Kickoff • United Men of Color Reception • The Peter Pan Project • CoSA Kickoff a Success • Power of Purple • Preview of The Laramie Project • Nutrition Tips • Inside Look at New Member Education • Opinions: Black History Month; Our Long-Awaited Greek Column • Heartbreak at Hopkins • Guntli Leading Rebounder • Senior Day Basketball Double-Headerhttps://digitalcommons.ursinus.edu/grizzlynews/1731/thumbnail.jp

The Grizzly, March 1, 2007

Media Lecture: The Jailhouse Doesn\u27t Rock • Peanut Butter Recall Update • Annual UC Job and Internship Fair • Living in Sin • Creating Communication Elation • Spotlight on Coach Kevin Small • Laramie Hits Big at Ursinus • Nutrition Tips: Fad Diets • Opinions: English as the Official Language? • Bears Capture Centennial Conference Title • Men\u27s Lacrosse Season Previewhttps://digitalcommons.ursinus.edu/grizzlynews/1733/thumbnail.jp

The Grizzly, February 8, 2007

WeCAN Protest for Workers\u27 Rights • Letters to the Editor • Class of \u2749 UC Alum Speaks on Women in World War II • Now That I\u27m Ready • What is an RA? • Note from the Editor: Facebook Fallacy • Nutrition Tips for the UC Student • UC Spotlight: UCEA • Opinions: The American Threat • Tumbling to Success • Rain, Rain and More Reignhttps://digitalcommons.ursinus.edu/grizzlynews/1730/thumbnail.jp

A Fine-grained Data Set and Analysis of Tangling in Bug Fixing Commits

Context: Tangled commits are changes to software that address multiple concerns at once. For researchers interested in bugs, tangled commits mean that they actually study not only bugs, but also other concerns irrelevant for the study of bugs. Objective: We want to improve our understanding of the prevalence of tangling and the types of changes that are tangled within bug fixing commits. Methods: We use a crowd sourcing approach for manual labeling to validate which changes contribute to bug fixes for each line in bug fixing commits. Each line is labeled by four participants. If at least three participants agree on the same label, we have consensus. Results: We estimate that between 17% and 32% of all changes in bug fixing commits modify the source code to fix the underlying problem. However, when we only consider changes to the production code files this ratio increases to 66% to 87%. We find that about 11% of lines are hard to label leading to active disagreements between participants. Due to confirmed tangling and the uncertainty in our data, we estimate that 3% to 47% of data is noisy without manual untangling, depending on the use case. Conclusion: Tangled commits have a high prevalence in bug fixes and can lead to a large amount of noise in the data. Prior research indicates that this noise may alter results. As researchers, we should be skeptics and assume that unvalidated data is likely very noisy, until proven otherwise.Comment: Status: Accepted at Empirical Software Engineerin

One Fish Two Fish Red Fish Blue Fish

One Fish Two Fish Red Fish Blue Fish was an entry in Myrin Library\u27s 3rd Annual Edible Books Festival at Ursinus Collegehttps://digitalcommons.ursinus.edu/ebf/1203/thumbnail.jp

One Flew Over the Cuckoo\u27s Nest

One Flew Over the Cuckoo\u27s Nest was an entry in Myrin Library\u27s 3rd Annual Edible Books Festival at Ursinus Collegehttps://digitalcommons.ursinus.edu/ebf/1199/thumbnail.jp

A fine-grained data set and analysis of tangling in bug fixing commits

Abstract Context: Tangled commits are changes to software that address multiple concerns at once. For researchers interested in bugs, tangled commits mean that they actually study not only bugs, but also other concerns irrelevant for the study of bugs. Objectives: We want to improve our understanding of the prevalence of tangling and the types of changes that are tangled within bug fixing commits. Methods: We use a crowd sourcing approach for manual labeling to validate which changes contribute to bug fixes for each line in bug fixing commits. Each line is labeled by four participants. If at least three participants agree on the same label, we have consensus. Results: We estimate that between 17% and 32% of all changes in bug fixing commits modify the source code to fix the underlying problem. However, when we only consider changes to the production code files this ratio increases to 66% to 87%. We find that about 11% of lines are hard to label leading to active disagreements between participants. Due to confirmed tangling and the uncertainty in our data, we estimate that 3% to 47% of data is noisy without manual untangling, depending on the use case. Conclusions: Tangled commits have a high prevalence in bug fixes and can lead to a large amount of noise in the data. Prior research indicates that this noise may alter results. As researchers, we should be skeptics and assume that unvalidated data is likely very noisy, until proven otherwise