Page 20 - 《软件学报》2025年第12期

于恒彪 等: 面向编译优化结果不一致的代码高效定位 5401

[16] Fousse L, Hanrot G, Lefèvre V, Pélissier P, Zimmermann P. MPFR: A multiple-precision binary floating-point library with correct
rounding. ACM Trans. on Mathematical Software (TOMS), 2007, 33(2): 13–es. [doi: 10.1145/1236463.1236468]
[17] Chiang WF, Gopalakrishnan G, Rakamaric Z, Solovyev A. Efficient search for inputs causing high floating-point errors. In: Proc. of the
19th ACM SIGPLAN Symp. on Principles and Practice of Parallel Programming. Orlando: ACM, 2014. 43–52. [doi: 10.1145/2555243.
2555265]
[18] Yi X, Chen LQ, Mao XG, Ji T. Efficient global search for inputs triggering high floating-point inaccuracies. In: Proc. of the 24th Asia-
Pacific Software Engineering Conf. Nanjing: IEEE, 2017. 11–20. [doi: 10.1109/APSEC.2017.7]
[19] Zou DM, Wang R, Xiong YF, Zhang L, Su ZD, Mei H. A genetic algorithm for detecting significant floating-point inaccuracies. In: Proc.
of the 37th IEEE/ACM Int’l Conf. on Software Engineering. Florence: IEEE, 2015. 529–539. [doi: 10.1109/ICSE.2015.70]
[20] Guo H, Rubio-González C. Efficient generation of error-inducing floating-point inputs via symbolic execution. In: Proc. of the 42nd Int’l
Conf. on Software Engineering. Seoul: IEEE, 2020. 1261–1272. [doi: 10.1145/3377811.3380359]
[21] Cadar C, Dunbar D, Engler D. KLEE: Unassisted and automatic generation of high-coverage tests for complex systems programs. In:
Proc. of the 8th USENIX Conf. on Operating Systems Design and Implementation. San Diego: USENIX Association, 2008. 209–224.
[22] Kaas RE, Carlin BP, Gelman A, Neal RM. Markov chain Monte Carlo in practice: A roundtable discussion. The American Statistician,
1998, 52(2): 93–100. [doi: 10.1080/00031305.1998.10480547]
[23] Miao D, Laguna I, Rubio-González C. Input range generation for compiler-induced numerical inconsistencies. In: Proc. of the 38th ACM
Int’l Conf. on Supercomputing. Kyoto: ACM, 2024. 201–212. [doi: 10.1145/3650200.3656618]
[24] Ren XL, Ho M, Ming J, Lei Y, Li L. Unleashing the hidden power of compiler optimization on binary code difference: An empirical
study. In: Proc. of the 42nd ACM SIGPLAN Int’l Conf. on Programming Language Design and Implementation. ACM, 2021. 142–157.
[doi: 10.1145/3453483.3454035]
[25] Wang R, Zou DM, He XR, Xiong YF, Zhang L, Huang G. Detecting and fixing precision-specific operations for measuring floating-point
errors. In: Proc. of the 24th ACM SIGSOFT Int’l Symp. on Foundations of Software Engineering. Seattle: ACM, 2016. 619–630. [doi: 10.
1145/2950290.2950355]
[26] IEEE. IEEE Std 754-2019 IEEE standard for floating-point arithmetic. 2019. https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=
&arnumber=8766229 [doi: 10.1109/IEEESTD.2019.8766229]
[27] Zhou H, Xue JL. Exploiting mixed SIMD parallelism by reducing data reorganization overhead. In: Proc. of the 2016 Int’l Symp. on
Code Generation and Optimization. Barcelona: ACM, 2016. 59–69. [doi: 10.1145/2854038.2854054]

于恒彪(1990－), 男, 博士, 副研究员, CCF 专业 黄春(1973－), 女, 博士, 研究员, 博士生导师, 主
会员, 主要研究领域为高性能计算, 程序分析. 要研究领域为高性能计算, 编译系统.

易昕(1992－), 男, 博士, 助理研究员, CCF 专业 尹帮虎(1989－), 男, 博士, 高级工程师, 主要研

会员, 主要研究领域为高性能计算, 程序分析. 究领域为高可信软件, 系统建模与仿真.

范小康(1987－), 男, 博士, 副研究员, 主要研究 王戟(1969－), 男, 博士, 研究员, 博士生导师,

领域为高性能计算, 编译优化. CCF 会士, 主要研究领域为软件方法学, 软件分
析与验证, 并行与分布计算.

唐滔(1984－), 男, 博士, 副研究员, 主要研究领

域为并行编程模型, 编译优化.