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<h3>Learning, optimization and hybrid approaches applied to software engineering</h3>
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<h3><b>Learning, optimization and hybrid approaches applied to software engineering</b></h3>
 
<i>Special Session</i> - 2nd International Conference on Learning and Optimization Algorithms: Theory and Applications ([http://lopal.org/ LOPAL])
 
<i>Special Session</i> - 2nd International Conference on Learning and Optimization Algorithms: Theory and Applications ([http://lopal.org/ LOPAL])
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<br />
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<p  style="color:#ff0000">Due to COVID-19, the conference has been postponed until 2021. A new CfP will be available as soon as the organizing committee announces new dates.</p>
  
 
==== Organization ====  
 
==== Organization ====  
  
<b>Location and dates: </b> C&oacute;rdoba, June 23th - 25th 2020.
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<b>Location and dates: </b> C&oacute;rdoba, 2021.
  
 
<b>Chairs</b>:
 
<b>Chairs</b>:
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==== Call for Papers ====  
 
==== Call for Papers ====  
  
TO DO
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From software conception to development, testing and delivery, software engineers constantly analyze project data and examine technological solutions to produce better products and services. In the last decades, machine learning (ML) and optimization techniques have been extensively studied seeking for new ways to automate software engineering (SE) tasks and help developers make better decisions.
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The aim of this special track is to bring together both experts and newcomers interested in the application of learning and optimization methods to software engineering, including search-based software engineering (SBSE), mining software repositories (MSR) and software analytics (SA). This special session seeks to promote the adoption of data-driven search-based software engineering, that is, enhancing SBSE methods with knowledge extracted by data mining techniques. Likewise, novel machine learning algorithms built or optimized by means of search techniques applied to software engineering activities are welcome too.
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The special session calls for relevant contributions proposing new or improved algorithms, as well as innovative applications. Submissions presenting emergent ideas and preliminary results on hybrid approaches are particularly encouraged.
  
 
<b>Topics of interest</b>
 
<b>Topics of interest</b>
  
TO DO
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The topics of interest for the special session include, but are not limited to, the following:
* Item1
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* Item2
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* Analysis and improvement of machine learning and optimization algorithms in the context of software engineering.
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* Applications of search-based methods in software engineering activities, such as software planning, analysis and design, coding and testing or software improvement. 
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* Applications of machine learning techniques in software projects, such as for fault prediction, effort estimation or software quality evaluation.
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* Approaches to enhance search-based methods with data extracted by machine learning techniques.
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* Use of optimization-based learning algorithms to improve knowledge extraction from software-related data.
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* Application of machine learning methods, such as clustering algorithms or deep learning, in relation to software analytics and mining software repositories.
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* New synergies between optimization and learning algorithms specifically designed to solve software engineering issues.
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* Search-based and ML-based recommendation systems for decision support in software development processes.
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* Advanced search techniques, including multi-objective optimization and human-in-the-loop approaches, to address software engineering tasks.
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* Empirical studies related to the introduction of learning and optimization techniques in software activities and projects in general, including risk or sensitivity analyses.
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* Case studies and industrial experiences related with the application of the aforementioned techniques.
  
 
==== Submission information and review process ====
 
==== Submission information and review process ====
TO DO
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Submissions will be done through the easychair platform, at the following [https://easychair.org/my/conference?conf=lopal2020# link]. Make sure you select the track name.
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Each paper will be reviewed by three reviewers on the basis of technical quality, relevance to special issue topics, originality, significance and clarity. Papers must be written in English following the [https://www.acm.org/publications/proceedings-template ACM template], with a maximum length of 6 pages. Additional information can be found [http://lopal.org/instructions-for-authors/submission/ here].
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At least, one author of an accepted paper shall register and attend the conference, in addition to presenting the paper. All accepted and presented papers will be published in the conference proceedings.
  
 
==== Important dates ====  
 
==== Important dates ====  
* Paper submission deadline: March 15th, 2020
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* Paper submission deadline: ''TBA''.
* Acceptance notification date: April 19th, 2020
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* Acceptance notification date: ''TBA''.
* Camera-ready due: May 3rd, 2020
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* Camera-ready due: ''TBA''.
* LOPAL conference: June 23th-25th, 2020
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* LOPAL conference: ''TBA''.
  
 
==== Technical review committee ====
 
==== Technical review committee ====
TO DO
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* Shaukat Ali (Simula Research Laboratory)
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* Wasif Afzal (M&auml;rlardalen University)
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* Francisco Chicano (University of M&aacute;laga)
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* Javier Ferrer (University of M&aacute;laga)
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* Antonio Garc&iacute;a-Dom&iacute;nquez (Aston University)
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* David G&oacute;mez-Ullate (University of C&aacute;diz)
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* Goran Mausa (University of Rijeka)
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* H&eacute;ctor Men&eacute;ndez (University College London)
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* Jos&eacute; Antonio Parejo (University of Sevilla)
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* Jos&eacute; Ra&uacute;l Romero (University of C&oacute;rdoba)
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* Sergio Segura (University of Sevilla)
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* Christopher Simons (University of the West of England)
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* Daniel Urda Mu&ntilde;oz (University of C&aacute;diz)

Revisión actual del 16:34 20 abr 2020


Learning, optimization and hybrid approaches applied to software engineering

Special Session - 2nd International Conference on Learning and Optimization Algorithms: Theory and Applications (LOPAL)

Due to COVID-19, the conference has been postponed until 2021. A new CfP will be available as soon as the organizing committee announces new dates.

Organization

Location and dates: Córdoba, 2021.

Chairs:

  • Aurora Ramírez (University of Córdoba) - email: aramirez at uco.es
  • Pedro Delgado-Pérez (University of Cádiz) - email: pedro.delgado at uca.es
  • Aitor Arrieta (Mondragon University) - email: aarrieta at mondragon.edu

Call for Papers

From software conception to development, testing and delivery, software engineers constantly analyze project data and examine technological solutions to produce better products and services. In the last decades, machine learning (ML) and optimization techniques have been extensively studied seeking for new ways to automate software engineering (SE) tasks and help developers make better decisions.

The aim of this special track is to bring together both experts and newcomers interested in the application of learning and optimization methods to software engineering, including search-based software engineering (SBSE), mining software repositories (MSR) and software analytics (SA). This special session seeks to promote the adoption of data-driven search-based software engineering, that is, enhancing SBSE methods with knowledge extracted by data mining techniques. Likewise, novel machine learning algorithms built or optimized by means of search techniques applied to software engineering activities are welcome too.

The special session calls for relevant contributions proposing new or improved algorithms, as well as innovative applications. Submissions presenting emergent ideas and preliminary results on hybrid approaches are particularly encouraged.

Topics of interest

The topics of interest for the special session include, but are not limited to, the following:

  • Analysis and improvement of machine learning and optimization algorithms in the context of software engineering.
  • Applications of search-based methods in software engineering activities, such as software planning, analysis and design, coding and testing or software improvement.
  • Applications of machine learning techniques in software projects, such as for fault prediction, effort estimation or software quality evaluation.
  • Approaches to enhance search-based methods with data extracted by machine learning techniques.
  • Use of optimization-based learning algorithms to improve knowledge extraction from software-related data.
  • Application of machine learning methods, such as clustering algorithms or deep learning, in relation to software analytics and mining software repositories.
  • New synergies between optimization and learning algorithms specifically designed to solve software engineering issues.
  • Search-based and ML-based recommendation systems for decision support in software development processes.
  • Advanced search techniques, including multi-objective optimization and human-in-the-loop approaches, to address software engineering tasks.
  • Empirical studies related to the introduction of learning and optimization techniques in software activities and projects in general, including risk or sensitivity analyses.
  • Case studies and industrial experiences related with the application of the aforementioned techniques.

Submission information and review process

Submissions will be done through the easychair platform, at the following link. Make sure you select the track name.

Each paper will be reviewed by three reviewers on the basis of technical quality, relevance to special issue topics, originality, significance and clarity. Papers must be written in English following the ACM template, with a maximum length of 6 pages. Additional information can be found here.

At least, one author of an accepted paper shall register and attend the conference, in addition to presenting the paper. All accepted and presented papers will be published in the conference proceedings.

Important dates

  • Paper submission deadline: TBA.
  • Acceptance notification date: TBA.
  • Camera-ready due: TBA.
  • LOPAL conference: TBA.

Technical review committee

  • Shaukat Ali (Simula Research Laboratory)
  • Wasif Afzal (Märlardalen University)
  • Francisco Chicano (University of Málaga)
  • Javier Ferrer (University of Málaga)
  • Antonio García-Domínquez (Aston University)
  • David Gómez-Ullate (University of Cádiz)
  • Goran Mausa (University of Rijeka)
  • Héctor Menéndez (University College London)
  • José Antonio Parejo (University of Sevilla)
  • José Raúl Romero (University of Córdoba)
  • Sergio Segura (University of Sevilla)
  • Christopher Simons (University of the West of England)
  • Daniel Urda Muñoz (University of Cádiz)