▷▷▷测试用例自动生成

测试用例自动生成是保障软件质量的重要环节。本实验室至2005年建立之初就开始从事软件测试自动生成方面的研究，在软件测试数据自动生成理论和实际应用开发方面积累了丰富的经验，取得了较好的研究成果。代表论文：

 ●Zhao Ruilian, Wang Weiwei, Song Yuqi, Li Zheng. Diversity-oriented test suite generation for EFSM model [J]. IEEE Transactions on Reliability. Accepted (DOI: 10.1109/ TR. 2020. 2971095).

 ●王微微, 李奕超, 赵瑞莲*, 李征. Web应用前后端融合的遗传算法并行化测试生成[J], 软件学报, 2020, (5).

 ●JunXia Guo, Zheng Li, CunFeng Shi RuiLian Zhao*, Thread Sche****ng Sequence Generate Based on All Synchronization Pair Coverage Criteria, International Journal of Software Engineering and Knowledge Engineering, 2020.

 ●Weiwei Wang, Xiaohong Guo, Zheng Li, and Ruilian Zhao*, Test Case Generation based on Client-Server of Web Applications by Memetic Algorithm, ISSRE 2019, The 30th International Symposium on Software Reliability Engineering, 2019, 1: 206-217.

 ●Junxia GUO, WeiWei Wang, Linjie Sun, Zheng Li and Ruilian Zhao. A Test Case Generation Method Based on State Importance of EFSM for Web Application. 30th International Conference on Software Engineering & Knowledge Engineering (SEKE 2018), pp.548-553, 2018.

 ●苏宁，郭俊霞，李征，赵瑞莲，基于EFSM不定型切片测试用例自动生成的研究，计算机研究与发展，2017，54(3)：669-680.

 ●Weiwei Wang, Ruilian Zhao*, Ying Shang, and Yong Liu,Test Data Generation Efficiency Prediction Model for EFSM Basedon MGGP, 8th International Symposium, SSBSE 2016,Raleigh, NC, USA, October 8–10,2016, 176-191.

 ●尤枫，赵瑞莲*，吕珊珊，基于输出域的测试用例自动生成方法研究，计算机研究与发展，2016，53（3）：1-9.

 ●Wei He, Ruilian Zhao*, Qunxiong Zhu, Integrating evolutionary testing with reinforcement learning for automated test generation of object-oriented software, Chinese Journal of Electronics. Vol.24, No.1, p38-48, Jan. 2015.

 ●Ruilian Zhao, Zheng Li and Qian Wang, Test Generation for Programs with Binary Tree Structure as Input , International Journal of Software Engineering and Knowledge Engineering, Vol. 25, No. 7 (2015) 1–23.

▷▷▷测试用例优先排序

课题组主要研究基于搜索的测试用例优先排序技术，提出上位性遗传算法, 解决TCP问题中所体现的上位性，实现了一个并行策略框架，并将二者整合为一个开源的原形工具；在持续集成环境下研究基于强化学习的测试用例排序技术，提出了基于历史信息、基于时间窗和基于出现频次等强化学习奖励机制。代表论文：

 ● Ying Shang, Qianyu Li, Yang Yang, Zheng Li. Occurrence Frequency and All Historical Failure Information Based Method for TCP in CI. ICSSP, Oct 2020. (To be appeared)

 ●Zhaolin Wu, Yang Yang, Zheng Li, and Ruilian Zhao. A Time Window based Reinforcement Learning Reward for Test Case Prioritization in Continuous Integration. Internetware 2019: 11th Asia-Pacific Symposium on Internetware, 2019

 ●何柳柳, 杨羊, 李征, 赵瑞莲. 面向持续集成测试优化的强化学习奖励机制. 软件学报, 2019,30(5):1438-1449

 ●Bian Yi, Li Zheng, Guo Junxia, Zhao Ruilian. Concrete hyperheuristic framework for test case prioritization. Journal of Software: Evolution and Process, v 30, n 11, November 2018

 ●Bian Yi , Li Zheng, Zhao Ruilian, Gong Dunwei.  Epistasis Based ACO for Regression Test Case Prioritization. IEEE Transactions on Emerging Topics in Computational Intelligence, v 1, n 3, p 213-223, June 2017

 ●边毅, 袁方, 郭俊霞, 李征, 赵瑞莲. 面向CPU+GPU异构计算的多目标测试用例优先排序, 软件学报, 2016, 27(4):943-954

 ●Fang Yuan, Yi Bian, Zheng Li and Ruilian Zhao, Epistatic Genetic Algorithm for Test Case Prioritization, Lecture Notes in Computer Science Volume 9275, pp 109-124, 2015

 ●Yi Bian , Serkan Kirbas, Mark Harman, Yue Jia, Zheng Li, Regression Test Case Prioritisation for Guava. Lecture Notes in Computer Science Volume 9275, pp 221-227, 2015

▷▷▷ 程序自动化错误定位

课题组主要研究基于变异的错误定位（MBFL）和基于程序谱的错误定位（SBFL）两种自动化错误定位技术。MBFL方面，针对该技术存在的执行开销大的问题，从测试用例优化、变异体约减、变异体执行优化等多个方面展开研究，在保证错误定位高精度的前提下，大幅度提升了执行效率。SBFL方面，从偶然正确测试用例识别与处理，多错误情况下的测试用例聚类等方面展开研究，提升了SBFL的错误定位效果。代表论文：

 ●[QRS2019]Zheng Li, Yonghao Wu, Yong Liu*. An Empirical Study of Bug Isolation on theEffectiveness of Multiple Fault Localization. IEEE International Conference on Software Quality, Reliability and Security. IEEE, 2019.

 ●[JSS2019]Yong Liu, Meiying Li, Yonghao Wu, Zheng Li*. A Weighted Fuzzy Classification Approach to Identify and Manipulate Coincidental Correct Test Cases for Fault Localization, Journal of Systems and Software, 2019(151):20-37

 ●[IS2018]Yong Liu, Zheng Li, Ruilian Zhao*, Pei Gong. An Optimal Mutation Execution Strategy for Cost Reduction of Mutation-Based Fault Localization, Information Science,2018(422):572-596

 ●[QRS2017]Yong Liu, Zheng Li, Linxin Wang, Ruilian Zhao*. Statement-Oriented Mutant Reduction Strategy for Mutation Based Fault Localization. IEEE International Conference on Software Quality, Reliability and Security. IEEE, 2017.

 ●[COMPSAC2017]Xiujing Liu, Yong Liu, Zheng Li, Ruilian Zhao. Fault Classification Oriented Spectrum Based Fault Localization. IEEE Computer Society Signature Conference on Computers, Software and Applications(COMPSAC). IEEE, 2017.

 ●[SATE2016]Zheng Li, Meiying Li, Yong Liu*, Jingyao Geng. Identify Coincidental Correct Test Cases Based on Fuzzy Classification. International Conference on Software Analysis, Testing and Evolution. IEEE, 2016:72-77.