publications

2026

1. Industrial Application of Deep Learning based Fault Localization with Mutation Features

   Heechan Yang, A. Lee, K. Cho , and Y. Kim

   In IEEE International Conference on Software Testing, Verification and Validation (ICST) Industry Track, May 2026

   Bib PDF Slides

   @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,
   }

2. Systematic Dataset Construction for Deep Learning-Based Fault Localization(DLFL) with Mutation-Based Fault Localization(MBFL) Features

   Heechan Yang

   Korean Advanced Institute of Science and Technology (KAIST), Feb 2026

   Bib PDF Slides

   @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,
   }

3. Systematic Study of Mutation-Based Dataset Construction for Deep Learning-Based Fault Localization on Military Defense SW

   Heechan Yang, A. Lee, K. Cho, and M. Kim

   Korean Conference on Software Engineering (KCSE), Feb 2026

   Bib PDF Slides

   @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},
   }

2024

1. How to Create Dataset to Train a ML Model for Fault Localization: A Case Study on JsonCpp

   Heechan Yang, A. Lee , I. Lee, H. Nam, N. Jung, K. Cho, and M. Kim

   Korean Computer Congress (KCC), Jun 2024

   Bib PDF

   @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},
   }

2022

1. A Neural Language Model-based Text Editing Tool for OCR Result of Unstructured Childhood Education Materials

   E. Ahn^*, Heechan Yang^*, E. Jee, and S. Hong

   Korean Software Congress (KSC), Dec 2022

   Note Awarded Bib PDF

   Undergraduate student research competition award

   * = Equal contribution

   @article{kcs22,
     title = {A Neural Language Model-based Text Editing Tool for OCR Result of Unstructured Childhood Education Materials},
     author = {Ahn, E. and Yang, Heechan and Jee, E. and Hong, S.},
     journal = {Korean Software Congress (KSC)},
     year = {2022},
     month = dec,
     pages = {1444--1446},
     note = {* = Equal contribution},
   }