|
Journal of Computer Science and Technology ›› 2022, Vol. 37 ›› Issue (1): 67-82.doi: 10.1007/s11390-021-1674-4
Special Issue: Software Systems
• Special Section on Software Systems 2021 • Previous Articles Next Articles
Que-Ping Kong1 (孔雀屏), Member, CCF, Zi-Yan Wang1 (王子彦), Member, CCF, Yuan Huang2 (黄袁), Member, CCF, Xiang-Ping Chen3,* (陈湘萍), Member, CCF, IEEE, Xiao-Cong Zhou1 (周晓聪), Member, CCF, Zi-Bin Zheng1 (郑子彬), Senior Member, CCF, ACM, IEEE, and Gang Huang4 (黄罡), Distinguished Member, CCF, Member, ACM, IEEE
[1] Zheng Z, Xie S, Dai H N, Chen W, Chen X, Weng J, Imran M. An overview on smart contracts: Challenges, advances and platforms. Future Generation Computer Systems, 2020, 105: 475-491. DOI: 10.1016/j.future.2019.12.019.
[2] Zheng P, Zheng Z, Wu J, Dai H N. XBlock-ETH: Extracting and exploring blockchain data from Ethereum. IEEE Open Journal of the Computer Society, 2020, 1: 95-106. DOI: 10.1109/OJCS.2020.2990458. [3] Albert E, Gordillo P, Rubio A, Schett M A. Synthesis of super-optimized smart contracts using Max-SMT. In Proc. the 32nd International Conference on Computer Aided Verification, Jul. 2020, pp.177-200. DOI: 10.1007/978-3-030-53288-8-10. [4] Nagele J, Schett M A. Blockchain superoptimizer. arXiv:2005.05912, 2020. https://arxiv.org/abs/2005.05912, May 2021. [5] Chen T, Li Z, Zhou H, Chen J, Luo X, Li X, Zhang X. Towards saving money in using smart contracts. In Proc. the 40th IEEE/ACM International Conference on Software Engineering: New Ideas and Emerging Technologies Results, May 27-Jun. 3, 2018, pp.81-84. DOI: 10.1145/3183399.3183420. [6] Chen T, Feng Y, Li Z, Zhou H, Luo X, Li X, Xiao X, Chen J, Zhang X. GasChecker: Scalable analysis for discovering gas-inefficient smart contracts. IEEE Transactions on Emerging Topics in Computing, 2020, 9(3): 1433-1448. DOI: 10.1109/TETC.2020.2979019. [7] Oliva G A, Hassan A E, Jiang Z M. An exploratory study of smart contracts in the Ethereum blockchain platform. Empirical Software Engineering, 2020, 25(3): 1864-1904. DOI: 10.1007/s10664-019-09796-5. [8] Durieux T, Ferreira J F, Abreu R, Cruz P. Empirical review of automated analysis tools on 47,587 Ethereum smart contracts. In Proc. the 42nd IEEE/ACM International Conference on Software Engineering, Oct. 2020, pp.530-541. DOI: 10.1145/3377811.3380364. [9] Chen J, Xia X, Lo D, Grundy J, Luo X, Chen T. Defining smart contract defects on Ethereum. IEEE Transactions on Software Engineering, 2022, 48(1): 327-345. DOI: 10.1109/TSE.2020.2989002. [10] Jiang B, Liu Y, Chan W. ContractFuzzer: Fuzzing smart contracts for vulnerability detection. In Proc. the 33rd IEEE/ACM International Conference on Automated Software Engineering, Sept. 2018, pp.259-269. DOI: 10.1145/3238147.3238177. [11] Grech N, Kong M, Jurisevic A, Brent L, Scholz B, Smaragdakis Y. MadMax: Surviving out-of-gas conditions in Ethereum smart contracts. Proceedings of the ACM on Programming Languages, 2018, 2(OOPSLA): Article No. 116. DOI: 10.1145/3276486. [12] Liu C, Liu H, Cao Z, Chen Z, Chen B, Roscoe B. ReGuard: Finding reentrancy bugs in smart contracts. In Proc. the 40th IEEE/ACM International Conference on Software Engineering: Companion, May 27-June 3, 2018, pp.65-68. DOI: 10.1145/3183440.3183495. [13] Li Z, Wu H, Xu J, Wang X, Zhang L, Chen Z. MuSC: A tool for mutation testing of Ethereum smart contract. In Proc. the 34th IEEE/ACM International Conference on Automated Software Engineering, Nov. 2019, pp.1198-1201. DOI: 10.1109/ASE.2019.00136. [14] Wang X, Wu H, Sun W, Zhao Y. Towards generating cost-effective test-suite for Ethereum smart contract. In Proc. the 26th IEEE International Conference on Software Analysis, Evolution and Reengineering, Feb. 2019, pp.549-553. DOI: 10.1109/SANER.2019.8668020. [15] Grech N, Brent L, Scholz B, Smaragdakis Y. Gigahorse: Thorough, declarative decompilation of smart contracts. In Proc. the 41st IEEE/ACM International Conference on Software Engineering, May 2019, pp.1176-1186. DOI: 10.1109/ICSE.2019.00120. [16] Chen T, Li X, Luo X, Zhang X. Under-optimized smart contracts devour your money. In Proc. the 24th IEEE International Conference on Software Analysis, Evolution and Reengineering, Feb. 2017, pp.442-446. DOI: 10.1109/SANER.2017.7884650. [17] Tikhomirov S, Voskresenskaya E, Ivanitskiy I, Takhaviev R, Marchenko E, Alexandrov Y. SmartCheck: Static analysis of Ethereum smart contracts. In Proc. the 1st International Workshop on Emerging Trends in Software Engineering for Blockchain, May 27-June 3, 2018, pp.9-16. DOI: 10.1145/3194113.3194115. [18] Zhang P, Xiao F, Luo X. SolidityCheck: Quickly detecting smart contract problems through regular s. arXiv:1911.09425, 2019. https://arxiv.org/abs/1911.09425, Nov. 2021. [19] Correas J, Gordillo P, Román-Díez G. Static profiling and optimization of Ethereum smart contracts using resource analysis. IEEE Access, 2021, 9: 25495-25507. DOI: 10.1109/ACCESS.2021.3057565. [20] Li Z, Chen T H, Yang J, Shang W. DLFinder: Characterizing and detecting duplicate logging code smells. In Proc. the 41st IEEE/ACM International Conference on Software Engineering, May 2019, pp.152-163. DOI: 10.1109/ICSE.2019.00032. [21] Vassallo C, Proksch S, Gall H C, Di Penta M. Automated reporting of anti-patterns and decay in continuous integration. In Proc. the 41st IEEE/ACM International Conference on Software Engineering, May 2019, pp.105-115. DOI: 10.1109/ICSE.2019.00028. [22] Afjehei S S, Chen T H, Tsantalis N. iPerfDetector: Characterizing and detecting performance antipatterns in iOS applications. Empirical Software Engineering, 2019, 24(6): 3484-3513. DOI: 10.1007/s10664-019-09703-y. [23] Dintyala P, Narechania A, Arulraj J. SQLCheck: Automated detection and diagnosis of SQL anti-patterns. In Proc. the 2020 ACM SIGMOD International Conference on Management of Data, Jun. 2020, pp.2331-2345. DOI: 10.1145/3318464.3389754. |
[1] | Peng-Fei Sun, Ya-Wen Ouyang, Ding-Jie Song, and Xin-Yu Dai. Self-Supervised Task Augmentation for Few-Shot Intent Detection [J]. Journal of Computer Science and Technology, 2022, 37(3): 527-538. |
[2] | Xin Feng, Hao-Ming Wu, Yi-Hao Yin, and Li-Bin Lan. CGTracker: Center Graph Network for One-Stage Multi-Pedestrian-Object Detection and Tracking [J]. Journal of Computer Science and Technology, 2022, 37(3): 626-640. |
[3] | Yan Tao, Yi-Teng Zhang, and Xue-Jin Chen. Element-Arrangement Context Network for Facade Parsing [J]. Journal of Computer Science and Technology, 2022, 37(3): 652-665. |
[4] | Jun Ma, Qing-Wei Sun, Chang Xu, and Xian-Ping Tao. GridDroid---An Effective and Efficient Approach for Android Repackaging Detection Based on Runtime Graphical User Interface [J]. Journal of Computer Science and Technology, 2022, 37(1): 147-181. |
[5] | Ze-Lin Zhao, Di Huang, and Xiao-Xing Ma. TOAST: Automated Testing of Object Transformers in Dynamic Software Updates [J]. Journal of Computer Science and Technology, 2022, 37(1): 50-66. |
[6] | Gen Zhang, Peng-Fei Wang, Tai Yue, Xu Zhou, Kai Lu. MEBS: Uncovering Memory Life-Cycle Bugs in Operating System Kernels [J]. Journal of Computer Science and Technology, 2021, 36(6): 1248-1268. |
[7] | Ling-Yun Situ, Zhi-Qiang Zuo, Le Guan, Lin-Zhang Wang, Xuan-Dong Li, Jin Shi, Peng Liu. Vulnerable Region-Aware Greybox Fuzzing [J]. Journal of Computer Science and Technology, 2021, 36(5): 1212-1228. |
[8] | Yu-Wei Wu, Qing-Gang Wang, Long Zheng, Xiao-Fei Liao, Hai Jin, Wen-Bin Jiang, Ran Zheng, Kan Hu. FDGLib: A Communication Library for Efficient Large-Scale Graph Processing in FPGA-Accelerated Data Centers [J]. Journal of Computer Science and Technology, 2021, 36(5): 1051-1070. |
[9] | Xiao-Jing Zha, Yin-Shui Xia, Shang-Luan Xie, Zhu-Fei Chu. Defect-Tolerant Mapping of CMOL Circuit Targeting Delay Optimization [J]. Journal of Computer Science and Technology, 2021, 36(5): 1118-1132. |
[10] | Hui-Ming Tian, Zhu-Fei Chu. Inversion Optimization Strategy Based on Primitives with Complement Attributes [J]. Journal of Computer Science and Technology, 2021, 36(5): 1145-1154. |
[11] | Dong-Hui Yang, Zhen-Yu Li, Xiao-Hui Wang, Kavé Salamatian, Gao-Gang Xie. Exploiting the Community Structure of Fraudulent Keywords for Fraud Detection in Web Search [J]. Journal of Computer Science and Technology, 2021, 36(5): 1167-1183. |
[12] | Yi-Xuan Tang, Zhi-Lei Ren, He Jiang, Xiao-Chen Li, Wei-Qiang Kong. An Empirical Comparison Between Tutorials and Crowd Documentation of Application Programming Interface [J]. Journal of Computer Science and Technology, 2021, 36(4): 856-876. |
[13] | Wen-Jun Yang, Bei-Ji Zou, Kai-Wen Li, Shu Liu. A Character Flow Framework for Multi-Oriented Scene Text Detection [J]. Journal of Computer Science and Technology, 2021, 36(3): 465-477. |
[14] | Yu-Jie Yuan, Yukun Lai, Tong Wu, Lin Gao, Li-Gang Liu. A Revisit of Shape Editing Techniques: From the Geometric to the Neural Viewpoint [J]. Journal of Computer Science and Technology, 2021, 36(3): 520-554. |
[15] | Jun Gao, Paul Liu, Guang-Di Liu, Le Zhang. Robust Needle Localization and Enhancement Algorithm for Ultrasound by Deep Learning and Beam Steering Methods [J]. Journal of Computer Science and Technology, 2021, 36(2): 334-346. |
|
|