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To improve software reliability, many rule-based techniques have been proposed to infer programming rules and detect violations of these rules as bugs. These rule-based approaches often rely on the highly frequent appearances of certain patterns in a project to infer rules. It is known that if a pattern does not appear frequently enough, rules are not learned, thus missing many bugs. In this paper,...
We propose and implement a new approach, Document-Assisted Symbolic Execution (DASE), to improve automated test generation and bug detection. DASE leverages natural language processing techniques and heuristics to analyze program documentation to extract input constraints automatically. DASE then uses the input constraints to guide symbolic execution to focus on inputs that are semantically more important...
Software performance is critical for how users perceive the quality of software products. Performance bugs — programming errors that cause significant performance degradation — lead to poor user experience and low system throughput. Designing effective techniques to address performance bugs requires a deep understanding of how performance bugs are discovered, reported, and fixed. In this paper, we...
Many bugs, even those that are known and documented in bug reports, remain in mature software for a long time due to the lack of the development resources to fix them. We propose a general approach, R2Fix, to automatically generate bug-fixing patches from free-form bug reports. R2Fix combines past fix patterns, machine learning techniques, and semantic patch generation techniques to fix bugs automatically...
Concurrency bugs in an operating system (OS) are detrimental as they can cause the OS to fail and affect all applications running on top of the OS. Detecting OS concurrency bugs is challenging due to the complexity of the OS synchronization, particularly with the presence of the OS specific interrupt context. Existing dynamic concurrency bug detection techniques are designed for user level applications...
Innovations from multiple directions have been proposed to improve software reliability. Unfortunately, many of the innovations are not fully exploited by programmers. To bridge the gap, this paper proposes a new approach to ldquolistenrdquo to thousands of programmers: studying their programming comments. Since comments express programmers' assumptions and intentions, comments can reveal programmers'...
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