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Single statement bugs are one of the most important ingredients in theevaluation of modern bug detection and automatic program repair methods. Byaffecting only a single statement, single statement bugs represent a type ofbug often overlooked by developers, while still being small enough to bedetected and fixed by automatic methods. With the rise of data-driven automaticrepair the availability of single statement bugs at the scale of millionth ofexamples is more important than ever; not only for testing these methods butalso for providing sufficient real world examples for training. To provideaccess to bug fix datasets of this scale, we are releasing two datasets calledSSB-9M and TSSB-3M. While SSB-9M provides access to a collection of over 9Mgeneral single statement bug fixes from over 500K open source Python projects ,TSSB-3M focuses on over 3M single statement bugs which can be fixed solely by asingle statement change. To facilitate future research and empiricalinvestigations, we annotated each bug fix with one of 20 single statement bug(SStuB) patterns typical for Python together with a characterization of thecode change as a sequence of AST modifications. Our initial investigation showsthat at least 40% of all single statement bug fixes mined fit at least oneSStuB pattern, and that the majority of 72% of all bugs can be fixed with thesame syntactic modifications as needed for fixing SStuBs.

TSSB-3M: Mining single statement bugs at massive scale