Orca: Differential Bug Localization In Large-Scale Services

Authors:
Ranjita Bhagwan Microsoft Research India
Rahul Kumar Microsoft Research India
Chandra Sekhar Maddila Microsoft Research India
Adithya Abraham Philip Microsoft Research India

Introduction:

Today, we depend on large-scale services for basic operations such as email.These services are extremely dynamic as developers continously commit code and introduce new features, fixes and new bugs.the authors have built Orca, a customized code search-engine that implements differential bug localization. We have built Orca, a customized code search-engine that implements differential bug localization.

Abstract:

Today, we depend on numerous large-scale services for basic operations such as email. These services are complex and extremely dynamic as developers continously commit code and introduce new features, fixes and, consequently, new bugs. Hundreds of commits may enter deployment simultaneously. Therefore one of the most time-critical, yet complex tasks towards mitigating service disruption is to localize the bug to the right commit.This paper presents the concept of differential bug localization that uses a combination of differential code analysis and software provenance tracking to effectively pin-point buggy commits. We have built Orca, a customized code search-engine that implements differential bug localization. Orca is actively being used by the On-Call Engineers (OCEs) of a large enterprise email and collaboration service to localize bugs to the appropriate buggy commits. Our evaluation shows that Orca correctly localizes 77% of bugs for which it has been used. We also show that it causes a 4x reduction in the work done by the OCE.

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