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One way to avoid overfitting is to filter out the generated patches. This can be done based on dynamic analysis.<ref>{{Cite journal|last1=Xin|first1=Qi|last2=Reiss|first2=Steven P.|date=2017-07-10|title=Identifying test-suite-overfitted patches through test case generation|url=http://dx.doi.org/10.1145/3092703.3092718|journal=Proceedings of the 26th ACM SIGSOFT International Symposium on Software Testing and Analysis|pages=226–236|___location=New York, NY, USA|publisher=ACM|doi=10.1145/3092703.3092718|isbn=978-1-4503-5076-1|s2cid=20562134}}</ref>
Alternatively, Tian et al. propose heuristic approaches to assess patch correctness. <ref>{{cite news |last1=Tian |first1=Haoye |last2=Liu |first2=Kui |last3=Kaboré |first3=Abdoul Kader |last4=Koyuncu |first4=Anil |last5=Li |first5=Li |last6=Klein |first6=Jacques |last7=Bissyandé |first7=Tegawendé F. |title=Evaluating representation learning of code changes for predicting patch correctness in program repair |url=https://dl.acm.org/doi/abs/10.1145/3324884.3416532 |work=Proceedings of the 35th IEEE/ACM International Conference on Automated Software Engineering |publisher=Association for Computing Machinery |date=27 January 2021 |pages=981–992 |doi=10.1145/3324884.3416532}}</ref><ref>{{cite journal |last1=Tian |first1=Haoye |last2=Tang |first2=Xunzhu |last3=Habib |first3=Andrew |last4=Wang |first4=Shangwen |last5=Liu |first5=Kui |last6=Xia |first6=Xin |last7=Klein |first7=Jacques |last8=BissyandÉ |first8=TegawendÉ F. |title=Is this Change the Answer to that Problem? Correlating Descriptions of Bug and Code Changes for Evaluating Patch Correctness |journal=Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering |date=5 January 2023 |pages=1–13 |doi=10.1145/3551349.3556914 |url=https://dl.acm.org/doi/abs/10.1145/3551349.3556914 |publisher=Association for Computing Machinery}}</ref>
== Limitations of automatic bug-fixing ==
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