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1. Bug synthesis: challenging bug-finding tools with deep faults

   https://doi.org/10.1145/3236024.3236084  

   Roy, Subhajit; Pandey, Awanish; Dolan-Gavitt, Brendan; Hu, Yu (November 2017, Proceedings of the 2018 26th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering)

   In spite of decades of research in bug detection tools, there is a surprising dearth of ground-truth corpora that can be used to evaluate the efficacy of such tools. Recently, systems such as LAVA and EvilCoder have been proposed to automatically inject bugs into software to quickly generate large bug corpora, but the bugs created so far differ from naturally occurring bugs in a number of ways. In this work, we propose a new automated bug injection system, Apocalypse, that uses formal techniques—symbolic execution, constraint-based program synthesis and model counting—to automatically inject fair (can potentially be discovered by current bug-detection tools), deep (requiring a long sequence of dependencies to be satisfied to fire), uncorrelated (each bug behaving independent of others), reproducible (a trigger input being available) and rare (can be triggered by only a few program inputs) bugs in large software code bases. In our evaluation, we inject bugs into thirty Coreutils programs as well as the TCAS test suite. We find that bugs synthesized by Apocalypse are highly realistic under a variety of metrics, that they do not favor a particular bug-finding strategy (unlike bugs produced by LAVA), and that they are more difficult to find than manually injected bugs, requiring up around 240× more tests to discover with a state-of-the-art symbolic execution tool. 

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2. Automatically Extracting Bug Reproducing Steps from Android Bug Reports

   Yu Zhao, Kye Miller (January 2019, International Conference on Software and Systems Reuse)
3. Bug Hunters’ Perspectives on the Challenges and Benefits of the Bug Bounty Ecosystem

   Akgul, Omer; Eghtesad, Taha; Elazari, Amit; Gnawali, Omprakash; Grossklags, Jens; Mazurek, Michelle L.; Votipka, Daniel; Laszka, Aron (July 2023, 32nd USENIX Security Symposium (USENIX Security 2023))

   Although researchers have characterized the bug-bounty ecosystem from the point of view of platforms and programs, minimal effort has been made to understand the perspectives of the main workers: bug hunters. To improve bug bounties, it is important to understand hunters’ motivating factors, challenges, and overall benefits. We address this research gap with three studies: identifying key factors through a free listing survey (n=56), rating each factor’s importance with a larger-scale factor-rating survey (n=159), and conducting semi-structured interviews to uncover details (n=24). Of 54 factors that bug hunters listed, we find that rewards and learning opportunities are the most important benefits. Further, we find scope to be the top differentiator between programs. Surprisingly, we find earning reputation to be one of the least important motivators for hunters. Of the challenges we identify, communication problems, such as unresponsiveness and disputes, are the most substantial. We present recommendations to make the bug-bounty ecosystem accommodating to more bug hunters and ultimately increase participation in an underutilized market. 

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4. On the relationship between bug reports and queries for text retrieval-based bug localization

   https://doi.org/10.1007/s10664-020-09823-w  

   Mills, Chris; Parra, Esteban; Pantiuchina, Jevgenija; Bavota, Gabriele; Haiduc, Sonia (September 2020, Empirical Software Engineering)

   null (Ed.)
5. Multiple siderophores: bug or feature?

   https://doi.org/10.1007/s00775-018-1617-x  

   McRose, Darcy L.; Seyedsayamdost, Mohammad R.; Morel, François M. (October 2018, JBIC Journal of Biological Inorganic Chemistry)