@inproceedings{080a131dc4b546d9a9c92a328a40d076,
title = "Template-guided concolic testing via online learning",
abstract = "We present template-guided concolic testing, a new technique for effectively reducing the search space in concolic testing. Addressing the path-explosion problem has been a significant challenge in concolic testing. Diverse search heuristics have been proposed to mitigate this problem but using search heuristics alone is not sufficient to substantially improve code coverage for real-world programs. The goal of this paper is to complement existing techniques and achieve higher coverage by exploiting templates in concolic testing. In our approach, a template is a partially symbolized input vector whose job is to reduce the search space. However, choosing a right set of templates is nontrivial and significantly affects the final performance of our approach. We present an algorithm that automatically learns useful templates online, based on data collected from previous runs of concolic testing. The experimental results with open-source programs show that our technique achieves greater branch coverage and finds bugs more effectively than conventional concolic testing.",
keywords = "Concolic Testing, Online Learning",
author = "Sooyoung Cha and Seonho Lee and Hakjoo Oh",
note = "Funding Information: This work was supported by Samsung Research Funding & Incubation Center of Samsung Electronics under Project Number SRFC-IT1701-09. This research was also supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (NRF-2016R1C1B2014062). Publisher Copyright: {\textcopyright} 2018 Association for Computing Machinery.; 33rd IEEE/ACM International Conference on Automated Software Engineering, ASE 2018 ; Conference date: 03-09-2018 Through 07-09-2018",
year = "2018",
month = sep,
day = "3",
doi = "10.1145/3238147.3238227",
language = "English",
series = "ASE 2018 - Proceedings of the 33rd ACM/IEEE International Conference on Automated Software Engineering",
publisher = "Association for Computing Machinery, Inc",
pages = "408--418",
editor = "Christian Kastner and Marianne Huchard and Gordon Fraser",
booktitle = "ASE 2018 - Proceedings of the 33rd ACM/IEEE International Conference on Automated Software Engineering",
}