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Professor Tracy Hall

Chair in Software Engineering

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  1. Journal article
  2. Published

    Automatically Identifying Code Features for Software Defect Prediction: Using AST N-grams

    Shippey, T., Bowes, D. & Hall, T., 02/2019, In: Information and Software Technology. 106, p. 142-160 19 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  3. Published

    Authors' reply to 'comments on 'researcher bias: The use of machine learning in software defect prediction''

    Shepperd, M., Hall, T. & Bowes, D., 1/11/2018, In: IEEE Transactions on Software Engineering. 44, 11, p. 1129-1131 3 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  4. Published

    Software defect prediction: do different classifiers find the same defects?

    Bowes, D., Hall, T. & Petrić, J., 1/06/2018, In: Software Quality Journal. 26, 2, p. 525-552 28 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  5. Published

    Biochar modulates heavy metal toxicity and improves microbial carbon use efficiency in soil

    Xu, Y., Seshadri, B., Sarkar, B., Wang, H., Rumpel, C., Sparks, D., Farrell, M., Hall, T., Yang, X. & Bolan, N., 1/12/2017, In: Science of the Total Environment. 621, p. 148-159 12 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  6. Published

    The relationship between evolutionary coupling and defects in large industrial software

    Kirbas, S., Caglayan, B., Hall, T., Counsell, S., Bowes, D., Sen, A. & Bener, A., 1/04/2017, In: Journal of Software: Evolution and Process. 29, 4, e1842.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  7. Published

    Evolutionary coupling measurement: Making sense of the current chaos

    Kirbas, S., Hall, T. & Sen, A., 15/02/2017, In: Science of Computer Programming. 135, p. 4-19 16 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  8. Published

    Some code smells have a significant but small effect on faults

    Hall, T., Bowes, D., Sun, Y. & Zhang, M., 08/2014, In: ACM Transactions on Software Engineering and Methodology. 23, 4, 39 p., 33.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  9. Published

    Researcher bias: The use of machine learning in software defect prediction

    Shepperd, M., Bowes, D. & Hall, T., 1/06/2014, In: IEEE Transactions on Software Engineering. 40, 6, p. 603-616 14 p., 6824804.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  10. Published

    DConfusion: A technique to allow cross study performance evaluation of fault prediction studies

    Bowes, D., Hall, T. & Gray, D., 04/2014, In: Automated Software Engineering. 21, 2, p. 287-313 27 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  11. Published

    Factors that motivate software engineering teams: A four country empirical study

    Verner, J. M., Babar, M. A., Cerpa, N., Hall, T. & Beecham, S., 25/01/2014, In: Journal of Systems and Software. 92, p. 115-127 13 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

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