References(49)
[4]
I. Nikolic A. Kolluri, I. Sergey, P. Saxena, and A. Hobor, Finding the greedy, prodigal, and suicidal contracts at scale, arXiv preprint arXiv: 1802.06038v2, 2018.
[8]
S. Kalra, S. Goel, M. Dhawan, and S. Sharma, ZEUS: Analyzing safety of smart contracts, in Network and Distributed System Security Symp., San Diego, CA, USA, .
[9]
H. Wu, X. Wang, J. Xu, W. Zou, L. Zhang, and Z. Chen, Mutation testing for ethereum smart contract, arXiv preprint arXiv: 1908.03707, 2019.
[12]
Y. Jia and M. Harman, An analysis and survey of the development of mutation testing, IEEE Trans. Software Eng., vol. 37, no. 5, pp. 649-678, 2011.
[13]
R. A. DeMillo, R. J. Lipton, and F. G. Sayward, Hints on test data selection: Help for the practicing programmer, Computer, vol. 11, no. 4, pp. 34-41, 1978.
[14]
A. J. Offutt, Investigations of the software testing coupling effect, ACM Trans. Software Eng. Methodol., vol. 1, no. 1, pp. 3-18, 1992.
[15]
R. Ma, S. Ren, K. Ma, C. Hu, and J. Xue, Semi-valid fuzz testing case generation for stateful network protocol, Tsinghua Science and Technology, vol. 22, no. 5, pp. 458-468, 2017.
[16]
L. M. Zhang, T. Xie, L. Zhang, N. Tillmann, J. De Halleux, and H. Mei, Test generation via dynamic symbolic execution for mutation testing, in Proc. 2010 IEEE Int. Conf. Software Maintenance, Timisoara, Romania, 2010.
[17]
M. C. Sánchez, J. M. C. de Gea, J. L. Fernández-Alemán, J. Garceran, and A. T. Sánchez. Software vulnerabilities overview: A descriptive study, Tsinghua Science and Technology, vol. 25, no. 2, pp. 270-280, 2020.
[18]
W. E. Wong and A. P. Mathur, Reducing the cost of mutation testing: An empirical study, J. Syst. Softw., vol. 31, no. 3, pp. 185-196, 1995.
[19]
P. G. Frankl, S. N. Weiss, and C. Hu, All-uses vs mutation testing: An experimental comparison of effectiveness, J. Syst. Softw., vol. 38, no. 3, pp. 235-253, 1997.
[20]
M. Polo, M. Piattini, and I. García-Rodríguez, Decreasing the cost of mutation testing with second-order mutants, Softw. Test. Verif. Reliab., vol. 19, no. 2, pp. 111-131, 2009.
[21]
H. Coles, T. Laurent, C. Henard, M. Papadakis, and A. Ventresque, PIT: A practical mutation testing tool for Java, in Proc. 25th Int. Symp, Saarbrücken, Germany, 2016.
[22]
A. Derezinska and A. Szustek, Object-oriented testing capabilities and performance evaluation of the C# mutation system, in Proc. 4th IFIP TC 2 Central and East European Conf. Software Engineering Techniques, Krakow, Poland, 2012, pp. 229-242.
[23]
P. Delgado-Pérez, I. Medina-Bulo, F. Palomo-Lozano, A. García-Domínguez, and J. J. Domínguez-Jiménez, Assessment of class mutation operators for C++ with the MuCPP mutation system, Inf. Softw. Technol., vol. 81, pp. 169-184, 2017.
[24]
Y. S. Ma, M. J. Harrold, and Y. R. Kwon, Evaluation of mutation testing for object-oriented programs, presented at 28th Int. Conf. Software Engineering, Shanghai, China, 2006.
[25]
S. W. Kim, J. A. Clark, and J. A. Mcdermid, Assessing test set adequacy for object-oriented programs using class mutation, presented at Symp. Class Mutation, York, England, 2016.
[26]
S. W. Kim, J. A. Clark, and J. A. Mcdermid, Class mutation: mutation testing for object-oriented programs, in Proc. Conf. Object-Oriented Software Systems, Erfurt, Germany, 2000.
[27]
K. Claessen and J. Hughes, QuickCheck: A lightweight tool for random testing of Haskell programs, ACM SIGPLAN Not., vol. 46, no. 4, pp. 268-279, 2000.
[28]
D. Le, M. A. Alipour, R. Gopinath, and A. Groce, MuCheck: An extensible tool for mutation testing of haskell programs, in Proc. 2014 Int. Symp. Software Testing and Analysis, San Jose, CA, USA, 2014.
[29]
L. Deng, N. Mirzaei, P. Ammann, and J. Offutt, Towards mutation analysis of Android apps, in Proc. 8th Int. Conf. Software Testing Verification and Validation Workshops (ICSTW), Graz, Austria, 2015.
[30]
K. Moran, M. Tufano, C. Bernal-Cárdenas, M. Linares-Vásquez, G. Bavota, C. Vendome, M. D. Penta, and D. Poshyvanyk, MDroid+: A mutation testing framework for android, in Proc. 2018 IEEE/ACM 40th Int. Conf. Software Engineering: Companion (ICSE-Companion), Gothenburg, Sweden, 2018.
[31]
S. Mirshokraie, A. Mesbah, and K. Pattabiraman, Guided mutation testing for JavaScript web applications, IEEE Trans. Softw. Eng., vol. 41, no. 5, pp. 429-444, 2015.
[32]
J. Chen, H. Wang, D. Towey, C. Mao, R. Huang, and Y. Zhan, Worst-input mutation approach to web services vulnerability testing based on SOAP messages, Tsinghua Science and Technology, vol. 19, no. 5, pp. 429-441, 2014.
[33]
Z. X. Li, H. R. Wu, J. H. Xu, X. Y. Wang, L. M. Zhang, and Z. Y. Chen, MuSC: A tool for mutation testing of ethereum smart contract, in Proc. 34th IEEE/ACM Int. Conf. Automated Software Engineering (ASE), San Diego, CA, USA, 2019.
[34]
P. Hartel and R. Schumi, Mutation testing of smart contracts at scale, arXiv preprint arXiv: 1909.12563, 2019.
[35]
E. Andesta, F. Faghih, and M. Fooladgar, Testing smart contracts gets smarter, arXiv preprint arXiv: 1912.04780, 2019.
[36]
L. Luu, D. H. Chu, H. Olickel, P. Saxena, and A. Hobor, Making smart contracts smarter, in Proc. 2016 ACM SIGSAC Conf. Computer and Communications Security, Vienna, Austria, 2016.
[37]
C. F. Torres, J. Schütte, and R. State, Osiris: Hunting for integer bugs in ethereum smart contracts, in Proc. 34th Ann. Computer Security Applications Conf. (ACSAC), San Juan, PR, USA, 2018.
[38]
K. Bhargavan, N. Swamy, S. Zanella-Béguelin, and A. Delignat-Lavaud, Formal verification of smart contracts: Short paper, in Proc. 34th Ann. Computer Security Applications Conf. (ACSAC’18), San Juan, PR, USA, 2016.
[40]
P. Tsankov, A. Dan, D. D. Cohen, A. Gervais, F. Buenzli, and M. Vechev, Securify: Practical security analysis of smart contracts, arXiv preprint arXiv: 1806.01143, 2018.
[41]
S. Tikhomirov, E. Voskresenskaya, I. Ivanitskiy, R. Takhaviev, E. Marchenko, and Y. Alexandrov, SmartCheck: Static analysis of ethereum smart contracts, in Proc. 2018 IEEE/ACM 1st Int. Workshop on Emerging Trends in Software Engineering for Blockchain (WETSEB), Gothenburg, Sweden, 2018.
[42]
P. C. Zhang, F. Xiao, and X. P. Luo, SolidityCheck: Quickly detecting smart contract problems through regular expressions, arXiv preprint arXiv: 1911.09425v1, 2019.
[43]
J. Feist, G. Grieco, and A. Groce, Slither: A static analysis framework for smart contracts, in Proc. 2019 IEEE/ACM 2nd Int. Workshop on Emerging Trends in Software Engineering for Blockchain (WETSEB), Montreal, Canada, 2019.
[44]
T. Durieux, J. F. Ferreira, R. Abreu, and P. Cruz, Empirical review of automated analysis tools on 47587 Ethereum Smart Contracts, arXiv preprint arXiv: 1910.10601, 2019.
[45]
B. Jiang, Y. Liu, and W. K. Chan, ContractFuzzer: Fuzzing smart contracts for vulnerability detection, presented at 2018 33rd IEEE/ACM Int. Conf. Automated Software Engineering (ASE), Montpellier, France, 2018.
[46]
H. J. Wang, Y. Li, S. W. Lin, C. Artho, L. Ma, and Y. Liu, Oracle-supported dynamic exploit generation for smart contracts, arXiv preprint arXiv: 1909.06605, 2019.
[47]
C. Liu, H. Liu, Z. Cao, Z. Chen, B. D. Chen, and B. Roscoe, ReGuard: Finding reentrancy bugs in smart contracts, in Proc. ACM/IEEE 40th Int. Conf. Software Engineering, Gothenburg, Sweden, 2018, pp. 65-68.