<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>0123-3033</journal-id>
<journal-title><![CDATA[Ingeniería y competitividad]]></journal-title>
<abbrev-journal-title><![CDATA[Ing. compet.]]></abbrev-journal-title>
<issn>0123-3033</issn>
<publisher>
<publisher-name><![CDATA[Facultad de Ingeniería, Universidad del Valle]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0123-30332023000300015</article-id>
<article-id pub-id-type="doi">10.25100/iyc.v25i3.13071</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[Architectural technical debt: an identification strategy]]></article-title>
<article-title xml:lang="es"><![CDATA[Deuda técnica en arquitectura: una estrategia de identificación]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Pérez]]></surname>
<given-names><![CDATA[Boris R.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad Francisco de Paula Santander Departamento de Sistemas e Informática ]]></institution>
<addr-line><![CDATA[Cúcuta ]]></addr-line>
<country>Colombia</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>12</month>
<year>2023</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>12</month>
<year>2023</year>
</pub-date>
<volume>25</volume>
<numero>3</numero>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_arttext&amp;pid=S0123-30332023000300015&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_abstract&amp;pid=S0123-30332023000300015&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_pdf&amp;pid=S0123-30332023000300015&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract Architectural Technical Debt is a metaphor for actions made by architects to achieve short-term goals while potentially harming the system&#8217;s long-term health. Architectural Technical Debt is difficult to detect since it is associated with a system&#8217;s long-term maintenance and evolution. In this research, we describe an architectural evolution-based method for debt identification that is backed by a supervised machine learning model and is based on information obtained from artifacts produced during architecture design. We discovered that even with a small amount of data, the machine learning model produces good results in terms of Recall and even Accuracy. The trial provides insights that allow us to conclude that this idea works well and might be utilized as a starting point to assist architects in identifying and managing Architectural Technical Debt.]]></p></abstract>
<abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen La deuda técnica en arquitectura es una metáfora de las decisiones tomadas por los arquitectos para alcanzar objetivos a corto plazo, pero que pueden dañar la salud del sistema a largo plazo. Esta deuda técnica es difícil de detectar, ya que está asociada a la mantenibilidad y la evolución de un sistema. En esta investigación, describimos un método basado en la evolución de la arquitectura para la identificación de la deuda que está respaldado por un modelo de aprendizaje automático supervisado y se basa en la información obtenida de los artefactos producidos durante el diseño de la arquitectura. Descubrimos que, incluso con una pequeña cantidad de datos, el modelo de aprendizaje automático produce buenos resultados en términos de Recall e incluso de Accuracy. Las experimentaciones realizadas proporcionaron información que nos permite concluir que esta idea funciona bien y podría utilizarse como punto de partida para ayudar a los arquitectos a identificar y gestionar la deuda técnica en arquitectura.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[Deuda técnica en arquitectura]]></kwd>
<kwd lng="es"><![CDATA[Estrategia de identificación]]></kwd>
<kwd lng="es"><![CDATA[Aprendizaje de máquina]]></kwd>
<kwd lng="es"><![CDATA[Arquitectura de software]]></kwd>
<kwd lng="en"><![CDATA[Architectural technical debt]]></kwd>
<kwd lng="en"><![CDATA[Identification strategy]]></kwd>
<kwd lng="en"><![CDATA[Machine learning]]></kwd>
<kwd lng="en"><![CDATA[Software architecture]]></kwd>
</kwd-group>
</article-meta>
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