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    <journal-meta />
    <article-meta>
      <contrib-group>
        <aff id="aff0">
          <label>0</label>
          <institution>Loïc</institution>
          ,
          <addr-line>Lagadec</addr-line>
        </aff>
        <aff id="aff1">
          <label>1</label>
          <institution>Université de Bretagne Occidentale</institution>
          ,
          <country country="FR">France</country>
        </aff>
      </contrib-group>
      <abstract>
        <p>The International Smalltalk Technologies Workshop (IWST) is a forum around advances or experience in Smalltalk, bringing together Smalltalk practitioners since 2009. The IWST aims to stimulate discussion and exchange of ideas on all aspects of Smalltalk, both theoretical and practical. IWST is a co-located event with the annual European Smalltalk User Group (ESUG) conference. The 2022 edition of IWST was held in Novi Sad, Serbia, July 24-26, with Lam Research Corporation as a sponsor.</p>
      </abstract>
      <kwd-group>
        <kwd>eol&gt;Smalltalk</kwd>
        <kwd>ESUG</kwd>
        <kwd>IWST</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>-</title>
      <p>Introduction to IWST 2022: a word from the editors</p>
    </sec>
    <sec id="sec-2">
      <title>1. Scope</title>
      <p>This report gathers six articles grouped into 3 categories of two papers each. The first one
is dedicated to performance: providing guidelines to achieve high performance, measuring
performance in AI. The second one deals with implementation and debugging in smalltalk
through two innovative axes: model-based delta-programming, and time-travelling debuggers.
The last category is dedicated to refactoring: transformation-based refactoring, and automatic
generation of class comments.</p>
    </sec>
    <sec id="sec-3">
      <title>2. Accepted papers</title>
      <p>Pharo environment, code comments are the primary form of code documentation and
typically convey information ranging from high-level design descriptions to low-level
implementation details. In this work, the authors adopt the stereotype-based approach to
automatically generate class comments in the pharo programming environment.</p>
    </sec>
    <sec id="sec-4">
      <title>Acknowledgments</title>
      <p>We would like to thank the Lam Research Corporation for their financial contribution to provide
awards for the best papers.</p>
    </sec>
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