Bebugging

Abstract: Compilers should be correct. To improve the quality of C compilers, we created Csmith, a randomized test-case generation tool, and spent three years using it to find compiler bugs. During this period we reported more than 325 previously unknown bugs to compiler developers. Every compiler we tested was found to crash and also to silently generate wrong code when presented with valid input. In this paper we present our compiler-testing tool and the results of our bug-hunting study. Our first contribution is to advance the state of the art in compiler testing. Unlike previous tools, Csmith generates programs that cover a large subset of C while avoiding the undefined and unspecified behaviors that would destroy its ability to automatically find wrong-code bugs. Our second contribution is a collection of qualitative and quantitative results about the bugs we have found in open-source C compilers.

Abstract: Memory access bugs, including buffer overflows and uses of freed heap memory, remain a serious problem for programming languages like C and C++. Many memory error detectors exist, but most of them are either slow or detect a limited set of bugs, or both. This paper presents AddressSanitizer, a new memory error detector. Our tool finds out-of-bounds accesses to heap, stack, and global objects, as well as use-after-free bugs. It employs a specialized memory allocator and code instrumentation that is simple enough to be implemented in any compiler, binary translation system, or even in hardware. AddressSanitizer achieves efficiency without sacrificing comprehensiveness. Its average slowdown is just 73% yet it accurately detects bugs at the point of occurrence. It has found over 300 previously unknown bugs in the Chromium browser and many bugs in other software.

Abstract: Many techniques have been developed over the years to automatically find bugs in software. Often, these techniques rely on formal methods and sophisticated program analysis. While these techniques are valuable, they can be difficult to apply, and they aren't always effective in finding real bugs.Bug patterns are code idioms that are often errors. We have implemented automatic detectors for a variety of bug patterns found in Java programs. In this extended abstract1, we describe how we have used bug pattern detectors to find serious bugs in several widely used Java applications and libraries. We have found that the effort required to implement a bug pattern detector tends to be low, and that even extremely simple detectors find bugs in real applications.From our experience applying bug pattern detectors to real programs, we have drawn several interesting conclusions. First, we have found that even well tested code written by experts contains a surprising number of obvious bugs. Second, Java (and similar languages) have many language features and APIs which are prone to misuse. Finally, that simple automatic techniques can be effective at countering the impact of both ordinary mistakes and misunderstood language features.

Abstract: The reality of multi-core hardware has made concurrent programs pervasive. Unfortunately, writing correct concurrent programs is difficult. Addressing this challenge requires advances in multiple directions, including concurrency bug detection, concurrent program testing, concurrent programming model design, etc. Designing effective techniques in all these directions will significantly benefit from a deep understanding of real world concurrency bug characteristics.This paper provides the first (to the best of our knowledge) comprehensive real world concurrency bug characteristic study. Specifically, we have carefully examined concurrency bug patterns, manifestation, and fix strategies of 105 randomly selected real world concurrency bugs from 4 representative server and client open-source applications (MySQL, Apache, Mozilla and OpenOffice). Our study reveals several interesting findings and provides useful guidance for concurrency bug detection, testing, and concurrent programming language design.Some of our findings are as follows: (1) Around one third of the examined non-deadlock concurrency bugs are caused by violation to programmers' order intentions, which may not be easily expressed via synchronization primitives like locks and transactional memories; (2) Around 34% of the examined non-deadlock concurrency bugs involve multiple variables, which are not well addressed by existing bug detection tools; (3) About 92% of the examined concurrency bugs canbe reliably triggered by enforcing certain orders among no more than 4 memory accesses. This indicates that testing concurrent programs can target at exploring possible orders among every small groups of memory accesses, instead of among all memory accesses; (4) About 73% of the examinednon-deadlock concurrency bugs were not fixed by simply adding or changing locks, and many of the fixes were not correct at the first try, indicating the difficulty of reasoning concurrent execution by programmers.