Supplementary materials of the paper entitled: "Generating Natural Language Requirements via Adversarial Examples in Deep Learning"

Supplementary materials of the paper entitled: "Generating Natural Language Requirements via Adversarial Examples in Deep Learning" File A: Datasets (.txt) A1: Webex A2: Zoom A3: Teams A4: Word A5: Power Point A6: Excel File B: Python Code (Both Ours and Baseline) B1: adversarial_samples.ipynb B2: Baseline.ipynb FIle C: Result Tables (.xlsx) C1: Table of Perturbed outputs in WebEx C2: Table of Perturbed outputs in Zoom C3: Table of Perturbed outputs in Teams C4: Table of Perturbed outputs in Word C5: Table of Perturbed outputs in Power Point C6: Table of Perturbed outputs in Excel (Excel) File D: Trend of Adversarial Shifts (Graphs) D1: Adversarial shifts of office suit (LSTM) D2: Adversarial shifts of video conferencing suit (LSTM) D3: Non-Adversarial shifts of office suit (LSTM) D4: Non-Adversarial shifts of video conferencing suit(LSTM) D5: Adversarial shifts of office suit (GRU) D6: Adversarial shifts of video conferencing suit (GRU) D7: Non-Adversarial shifts of office suit (GRU) D8: Non-Adversarial shifts of video conferencing suit(GRU) D9: Adversarial shifts of office suit (Bi-LSTM) D10: Adversarial shifts of video conferencing suit (Bi-LSTM) D11: Non-Adversarial shifts of office suit (Bi-LSTM) D12: Non-Adversarial shifts of video conferencing suit(Bi-LSTM) File E: Adversarial Examples (.pdf) E1: Adversarial vs Original in WebEx E2: Adversarial vs Original in Zoom E3: Adversarial vs Original in Teams E4: Adversarial vs Original in Word E5: Adversarial vs Original in Power Point E6: Adversarial vs Original in Excel File F: Questionnaire <br> <br> <br> <br> <br> <br>本论文题为《基于深度学习对抗样本生成自然语言需求》的补充材料。 文件A：数据集（.txt格式） A1：Webex A2：Zoom A3：Teams A4：Word A5：PowerPoint A6：Excel 文件B：Python代码（涵盖本文提出方法与基线方法） B1：adversarial_samples.ipynb B2：Baseline.ipynb 文件C：结果表格（.xlsx格式） C1：Webex扰动输出结果表 C2：Zoom扰动输出结果表 C3：Teams扰动输出结果表 C4：Word扰动输出结果表 C5：PowerPoint扰动输出结果表 C6：Excel扰动输出结果表 文件D：对抗偏移趋势（图表） D1：办公套件对抗偏移（长短期记忆网络（LSTM）） D2：视频会议套件对抗偏移（长短期记忆网络（LSTM）） D3：办公套件非对抗偏移（长短期记忆网络（LSTM）） D4：视频会议套件非对抗偏移（长短期记忆网络（LSTM）） D5：办公套件对抗偏移（门控循环单元（GRU）） D6：视频会议套件对抗偏移（门控循环单元（GRU）） D7：办公套件非对抗偏移（门控循环单元（GRU）） D8：视频会议套件非对抗偏移（门控循环单元（GRU）） D9：办公套件对抗偏移（双向长短期记忆网络（Bi-LSTM）） D10：视频会议套件对抗偏移（双向长短期记忆网络（Bi-LSTM）） D11：办公套件非对抗偏移（双向长短期记忆网络（Bi-LSTM）） D12：视频会议套件非对抗偏移（双向长短期记忆网络（Bi-LSTM）） 文件E：对抗样本（.pdf格式） E1：Webex对抗样本与原始样本对比 E2：Zoom对抗样本与原始样本对比 E3：Teams对抗样本与原始样本对比 E4：Word对抗样本与原始样本对比 E5：PowerPoint对抗样本与原始样本对比 E6：Excel对抗样本与原始样本对比 文件F：调查问卷