A large scale study of programming languages and code quality in github

B Ray, D Posnett, V Filkov, P Devanbu - Proceedings of the 22nd ACM …, 2014 - dl.acm.org
What is the effect of programming languages on software quality? This question has been a
topic of much debate for a very long time. In this study, we gather a very large data set from …

An empirical analysis of flaky tests

Q Luo, F Hariri, L Eloussi, D Marinov - Proceedings of the 22nd ACM …, 2014 - dl.acm.org
Regression testing is a crucial part of software development. It checks that software changes
do not break existing functionality. An important assumption of regression testing is that test …

A comprehensive study of deep learning compiler bugs

Q Shen, H Ma, J Chen, Y Tian, SC Cheung… - Proceedings of the 29th …, 2021 - dl.acm.org
There are increasing uses of deep learning (DL) compilers to generate optimized code,
boosting the runtime performance of DL models on specific hardware. Like their traditional …

Understanding and detecting real-world performance bugs

G **, L Song, X Shi, J Scherpelz, S Lu - ACM SIGPLAN Notices, 2012 - dl.acm.org
Developers frequently use inefficient code sequences that could be fixed by simple patches.
These inefficient code sequences can cause significant performance degradation and …

Learning from mistakes: a comprehensive study on real world concurrency bug characteristics

S Lu, S Park, E Seo, Y Zhou - … of the 13th international conference on …, 2008 - dl.acm.org
The reality of multi-core hardware has made concurrent programs pervasive. Unfortunately,
writing correct concurrent programs is difficult. Addressing this challenge requires advances …

Predicting defects using network analysis on dependency graphs

T Zimmermann, N Nagappan - … of the 30th international conference on …, 2008 - dl.acm.org
In software development, resources for quality assurance are limited by time and by cost. In
order to allocate resources effectively, managers need to rely on their experience backed by …

Personalized defect prediction

T Jiang, L Tan, S Kim - 2013 28th IEEE/ACM International …, 2013 - ieeexplore.ieee.org
Many defect prediction techniques have been proposed. While they often take the author of
the code into consideration, none of these techniques build a separate prediction model for …

Repairing deep neural networks: Fix patterns and challenges

MJ Islam, R Pan, G Nguyen, H Rajan - Proceedings of the ACM/IEEE …, 2020 - dl.acm.org
Significant interest in applying Deep Neural Network (DNN) has fueled the need to support
engineering of software that uses DNNs. Repairing software that uses DNNs is one such …

Predicting vulnerable software components

S Neuhaus, T Zimmermann, C Holler… - Proceedings of the 14th …, 2007 - dl.acm.org
Where do most vulnerabilities occur in software? Our Vulture tool automatically mines
existing vulnerability databases and version archives to map past vulnerabilities to …

Bug characteristics in open source software

L Tan, C Liu, Z Li, X Wang, Y Zhou, C Zhai - Empirical software …, 2014 - Springer
To design effective tools for detecting and recovering from software failures requires a deep
understanding of software bug characteristics. We study software bug characteristics by …