Reverse Engineering Variability from Natural Language Documents: A Systematic Literature Review. - Yang Li 060; Sandro Schulze; Gunter Saake (SPLC (A), 2017)

Feature and variability extraction from natural language software requirements specifications. - Yang Li 060 (SPLC (2), 2018)

Reverse engineering variability from requirement documents based on probabilistic relevance and word embedding. - Yang Li 060; Sandro Schulze; Gunter Saake (SPLC, 2018)

Extracting features from requirements: Achieving accuracy and automation with neural networks. - Yang Li 060; Sandro Schulze; Gunter Saake (SANER, 2018)

The Best of Both Worlds: Combining Hand-Tuned and Word-Embedding-Based Similarity Measures for Entity Resolution. - Xiao Chen 008; Gabriel Campero Durand; Roman Zoun; David Broneske; Yang Li 060; Gunter Saake (BTW, 2019)

Feature Terms Prediction: A Feasible Way to Indicate the Notion of Features in Software Product Line. - Yang Li 060; Sandro Schulze; Jiahua Xu (EASE, 2020)

Automated extraction of domain knowledge in practice: the case of feature extraction from requirements at danfoss. - Yang Li 060; Sandro Schulze; Helene Hvidegaard Scherrebeck; Thomas Sorensen Fogdal (SPLC (A), 2020)

Automated extraction of feature and variability information from natural language requirement specifications. - Yang Li 060 (2020)

Feature and Variability Extraction from Natural Language Requirements. - Sandro Schulze; Yang Li 060 (Handbook of Re-Engineering Software Intensive Systems into Software Product Lines, 2023)