Heechan Yang

@inproceedings{ase26,
  title = {Top-down Multi-agent LLM System with Runtime Data for MISRA C Violation Detection},
  author = {Lee, A. and Kang, Y. and Jang, S. and Yang, H. and Kim, M.},
  booktitle = {IEEE/ACM International Conference on Automated Software Engineering (ASE) Industry Track},
  year = {2026},
  month = oct,
}

@inproceedings{icst26,
  title = {Industrial Application of Deep Learning based Fault Localization with Mutation Features},
  author = {Yang, Heechan and Lee, A. and Cho, K. and Kim, Y.},
  booktitle = {IEEE International Conference on Software Testing, Verification and Validation (ICST) Industry Track},
  year = {2026},
  month = may,
}

@thesis{ms2026,
  title = {Systematic Dataset Construction for Deep Learning-Based Fault Localization(DLFL) with Mutation-Based Fault Localization(MBFL) Features},
  author = {Yang, Heechan},
  school = {Korean Advanced Institute of Science and Technology (KAIST)},
  year = {2026},
  month = feb,
}

@article{kcse26,
  title = {Systematic Study of Mutation-Based Dataset Construction for Deep Learning-Based Fault Localization on Military Defense SW},
  author = {Yang, Heechan and Lee, A. and Cho, K. and Kim, M.},
  journal = {Korean Conference on Software Engineering (KCSE)},
  year = {2026},
  month = feb,
  volumn = {28},
  number = {1},
  pages = {145--148},
}

@article{kcc24,
  title = {How to Create Dataset to Train a ML Model for Fault Localization: A Case Study on JsonCpp},
  author = {Yang, Heechan and Lee, A. and Lee, I. and Nam, H. and Jung, N. and Cho, K. and Kim, M.},
  journal = {Korean Computer Congress (KCC)},
  year = {2024},
  month = jun,
  pages = {331--333},
}