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        <datestamp>2021-12-23T09:35:12Z</datestamp>
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          <dc:title>MLCatchUp: Automated update of deprecated machine-learning APIs in Python</dc:title>
          <dc:creator>Stefanus AGUS HARYONO (8644332)</dc:creator>
          <dc:creator>Thung Ferdian (8642442)</dc:creator>
          <dc:creator>David LO (8645202)</dc:creator>
          <dc:creator>Julia LAWALL (11871853)</dc:creator>
          <dc:creator>Lingxiao JIANG (8645670)</dc:creator>
          <dc:subject>Knowledge representation and reasoning</dc:subject>
          <dc:subject>python</dc:subject>
          <dc:subject>machine learning libraries</dc:subject>
          <dc:subject>Knowledge Representation and Machine Learning</dc:subject>
          <dc:description>&lt;div&gt;MLCatchUp provide an automated approach in the update of deprecated Python API usages. MLCatchUp infers the required transformation for the API update based on the differences between the deprecated and updated API signatures. This transformation operations are presented by MLCatchUp in DSL (domain specific language) script.&lt;/div&gt;&lt;div&gt;&lt;div&gt;&lt;br&gt;&lt;/div&gt;&lt;div&gt;There are two main functionalities within MLCatchUp:&lt;/div&gt;&lt;div&gt;&lt;br&gt;&lt;/div&gt;&lt;div&gt;1. Transformation Inference Use the deprecated and updated API signatures mapping to create the DSL script that is used&lt;/div&gt;&lt;div&gt;2. Transformation Application Applies the created DSL script into the target file, updating all the specified deprecated APIs according to the inferred transformation operations.&lt;/div&gt;&lt;/div&gt;</dc:description>
          <dc:date>2021-12-23T09:35:12Z</dc:date>
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