• The KIPS Transactions:PartA
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• v.18A no.2
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• pp.61-68
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• 2011

Memory error debugging is one of the most critical processes in improving software quality. However, due to the extensive time consumed to debug, the enhancement often leads to a huge bottle neck in the development process of mobile devices. Most of the existing memory error detection tools are based on static error detection; however, the tools cannot be used in mobile devices due to their use of large working memory. Therefore, it is challenging for mobile device vendors to deliver high quality mobile devices to the market in time. In this paper, we introduce "PinMemcheck", a pin-based memory error detection tool, which detects all potential memory errors within $1.5{\times}$ execution time overhead compared with that of a baseline configuration by applying the Pin's binary instrumentation process and a simple data structure.

• Journal of KIISE:Software and Applications
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• v.34 no.8
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• pp.708-720
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• 2007

Memory access errors are frequently occurred in computer programs written in C programming language [1,2]. Accordingly, a number of research works have suggested a wide variety of methods to detect such errors automatically. However, they have one or more of the following problems: inability to detect all memory errors, changing the memory allocation mechanism, and excessive performance overhead. To cope with these problems, in this paper we suggest a new and automated tool to detect dynamic memory access errors in C programs.

• The KIPS Transactions:PartD
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• v.14D no.6
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• pp.675-688
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• 2007

Memory access errors are frequently occurred in C programs. A number of tools and research works have been trying to detect the errors automatically. However, they have one or more of the following problems: inability to detect all memory errors, changing the memory allocation mechanism, incompatibility with libraries, and excessive performance overhead. In this paper, we suggest a new method to solve these problems, and then present a result of comparison to the previous research works through the experiments. Our approach consists of two phases. First is to transform source code at compile time through inserting instrumentation into the source code. And second is to detect memory errors at run time with a bitmap that maintains information about memory allocation. Our approach has improved the error detection abilities against the binary code analysis based ones by using the source code analysis technique, and enhanced performance in terms of both space and time, too. In addition, our approach has no problem with respect to compatibility with shared libraries as well as does not need to modify memory allocation mechanism.