1. Department of Computer Science, Shanghai Jiao Tong University, Shanghai 200240, China 2. School of Software, Shanghai Jiao Tong University, Shanghai 200240, China 3. Intel Asia-Pacific Research and Development Ltd., Shanghai 200240, China 4. Department of Advanced Information Technology, Kyushu University, Fukuoka 819-0395, Japan
Symbolic execution is widely used in many code analysis, testing, and verification tools. As symbolic execution exhaustively explores all feasible paths, it is quite time consuming. To handle the problem, researchers have paralleled existing symbolic execution tools (e.g., KLEE). In particular, Cloud9 is a widely used paralleled symbolic execution tool, and researchers have used the tool to analyze real code. However, researchers criticize that tools such as Cloud9 still cannot analyze large scale code. In this paper, we conduct a field study on Cloud9, in which we use KLEE and Cloud9 to analyze benchmarks in C. Our results confirm the criticism. Based on the results, we identify three bottlenecks that hinder the performance of Cloud9: the communication time gap, the job transfer policy, and the cache management of the solved constraints. To handle these problems, we tun the communication time gap with better parameters, modify the job transfer policy, and implement an approach for cache management of solved constraints. We conduct two evaluations on our benchmarks and a real application to understand our improvements. Our results show that our tuned Cloud9 reduces the execution time significantly, both on our benchmarks and the real application. Furthermore, our evaluation results show that our tuning techniques improve the effectiveness on all the devices, and the improvement can be achieved upto five times, depending upon a tuning value of our approach and the behaviour of program under test.
Ciortea L, Zamfir C, Bucur S, Chipounov V, Candea G. Cloud9: a software testing service. ACM SIGOPS Operating Systems Review, 2010, 43(4): 5–10 https://doi.org/10.1145/1713254.1713257
2
Staats M, Pˇašareanu C S. Parallel symbolic execution for structural testgeneration. In: Proceedings of the 19th International Symposium on Software Testing and Analysis. 2010, 183–194
3
King A. Distributed parallel symbolic execution. Dissertation for the Doctoral Degree. Manhattan, KS: Kansas State University, 2009
4
Siddiqui J H, Khurshid S. ParSym: Parallel symbolic execution. In: Proceedings of the 2nd International Conference on Software Technology and Engineering. 2010, 405–409 https://doi.org/10.1109/ICSTE.2010.5608866
5
Sasnauskas R, Dustmann O S, Kaminski B L, Wehrle K, Weise C, Kowalewski S. Scalable symbolic execution of distributed systems. In: Proceedings of the 31st International Conference on Distributed Computing Systems. 2011, 333–342 https://doi.org/10.1109/ICDCS.2011.28
6
Griesmayer A, Aichernig B, Johnsen E B, Schlatte R. Dynamic symbolic execution of distributed concurrent objects. In: Lee D, Lopes A, Poetzsch-Heffter A, eds. Formal Techniques for Distributed Systems. Berlin: Springer, 2009, 225–230 https://doi.org/10.1007/978-3-642-02138-1_16
7
Aleb N, Kechid S. A new approach for distributed symbolic software testing. In: Proceedings of International Conference on Computational Science and Its Applications. 2013, 487–497 https://doi.org/10.1007/978-3-642-39643-4_35
8
Cadar C, Dunbar D, Engler D R. KLEE: unassisted and automatic generation of high-coverage tests for complex systems programs. In: Proceeding of OSDI. 2008, 209–224
9
Bucur S, Ureche V, Zamfir C, Candea G. Parallel symbolic execution for automated real-world software testing. In: Proceedings of the 6th ACM Conference on Computer Systems. 2011, 183–198 https://doi.org/10.1145/1966445.1966463
10
Candea G, Bucur S, Zamfir C. Automated software testing as a service. In: Proceedings of the 1st ACM Symposium on Cloud Computing. 2010, 155–160 https://doi.org/10.1145/1807128.1807153
11
Renshaw D, Kong S. Symbolic execution in difficult environments. Technical Report 15-745. 2011
12
Marinescu P D, Cadar C. Make test-zesti: A symbolic execution solution for improving regression testing. In: Proceedings of the 34th International Conference on Software Engineering. 2012, 716–726 https://doi.org/10.1109/ICSE.2012.6227146
13
Cui H M, Hu G, Wu J Y, Yang J. Verifying systems rules using ruledirected symbolic execution. ACM SIGPLAN Notices, 2013, 48(4): 329–342 https://doi.org/10.1145/2499368.2451152
14
Zhang D Z, Liu D G, Lei Y, Kung D, Csallner C, Wang W H. Detecting vulnerabilities in c programs using trace-based testing. In: Proceedings of IEEE/IFIP International Conference on Dependable Systems and Networks. 2010, 241–250
15
Zitser M, Lippmann R, Leek T. Testing static analysis tools using exploitable buffer overflows from open source code. ACM SIGSOFT Software Engineering Notes, 2004, 29(6): 97–106 https://doi.org/10.1145/1041685.1029911
16
Saxena P, Poosankam P, McCamant S, Song D. Loop-extended symbolic execution on binary programs. In: Proceedings of the 18th ACM International Symposium on Software Testing and Analysis. 2009, 225–236 https://doi.org/10.21236/ADA538843
17
Jaffar J, Murali V, Navas J A, Santosa A E. TRACER: a symbolic execution tool for verification. In: Proceedings of the 24th International Conference on Computer Aided Verification. 2012, 758–766 https://doi.org/10.1007/978-3-642-31424-7_61
Sen K, Marinov D, Agha G. CUTE: a concolic unit testing engine for C. ACMSIGSOFT Software Engineering Notes, 2005, 30(5): 263–272 https://doi.org/10.1145/1095430.1081750
21
Zhang Y F, Chen Z B, Wang J. Speculative symbolic execution. In: Proceedings of the 23rd IEEE International Symposium on Software Reliability Engineering. 2012, 101–110 https://doi.org/10.1109/ISSRE.2012.8
22
Palikareva H, Cadar C. Multi-solver support in symbolic execution. In: Proceedings of International Conference on Computer Aided Verification. 2013, 53–68 https://doi.org/10.1007/978-3-642-39799-8_3