IntPTI: Automatic integer error repair with proper-type inference
Title | IntPTI: Automatic integer error repair with proper-type inference |
Publication Type | Conference Paper |
Year of Publication | 2017 |
Authors | Cheng, X., Zhou, M., Song, X., Gu, M., Sun, J. |
Conference Name | 2017 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE) |
Date Published | oct |
ISBN Number | 978-1-5386-2684-9 |
Keywords | Computer bugs, fix pattern, integer error, maintenance engineering, pubcrawl, Runtime, Scalability, security, security scalability, Semantics, Tools, type inference |
Abstract | Integer errors in C/C++ are caused by arithmetic operations yielding results which are unrepresentable in certain type. They can lead to serious safety and security issues. Due to the complicated semantics of C/C++ integers, integer errors are widely harbored in real-world programs and it is error-prone to repair them even for experts. An automatic tool is desired to 1) automatically generate fixes which assist developers to correct the buggy code, and 2) provide sufficient hints to help developers review the generated fixes and better understand integer types in C/C++. In this paper, we present a tool IntPTI that implements the desired functionalities for C programs. IntPTI infers appropriate types for variables and expressions to eliminate representation issues, and then utilizes the derived types with fix patterns codified from the successful human-written patches. IntPTI provides a user-friendly web interface which allows users to review and manage the fixes. We evaluate IntPTI on 7 real-world projects and the results show its competitive repair accuracy and its scalability on large code bases. The demo video for IntPTI is available at: https://youtu.be/9Tgd4A\_FgZM. |
URL | https://ieeexplore.ieee.org/document/8115718 |
DOI | 10.1109/ASE.2017.8115718 |
Citation Key | cheng_intpti:_2017 |