Francis Palma

Francis Palma

Institutionen för datavetenskap och medieteknik Fakulteten för teknik
14073, Hus Magna, Kalmar
A34.23, Hus Magna, Kalmar
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I am an Assistant Professor (Universitetslektor in Sweden and Senior Lecturer in UK) in the Department of Computer Science and Media Technology at the Linnaeus University in Kalmar, Sweden.

Before joining Linnaeus University, until October 2018, I worked as a Postdoctoral Research Fellow in Ryerson University with Dr. Ayse Bener as a team member of her Data Science Laboratory (DSL) with an IBM CAS project on applying Machine Learning techniques in prioritizing test cases in the context of software development and testing. Previously, I was working as a Research Scientist with a focus on the Big Data and Machine Learning at the Screaming Power Inc. I also worked as a Postdoctoral Research Fellow at the Concordia University in the Department of Electrical & Computer Engineering (ECE) under the supervision of Dr. Ferhat Khendek (Concordia) and Dr. Maria Toeroe (Ericsson Canada Inc, Montreal). I was a member of MAGIC team at Concordia/Ericsson.

In August 2015, I had PhD from Ecole Polytechnique de Montreal, Canada under the supervision of Dr. Naouel Moha and Dr. Yann-Gaël Guéhéneuc. My main research interests included Service Oriented Architecture (SOA) Antipatterns and Quality of Service (QoS) for Service-based Systems (SBSs). I was a member of Ptidej Team and LATECE Lab.

Further information is available on my Web site or on my LinkedIn


I teach the following course(s) at the Linnaeus University:

- 2DV608 Software Engineering - Design – 7.5 credits (Bachelor level) - Requirement Engineering module
- 4ME307 Internet Architectures – 7.5 credits (Master’s level)
- 1DV510 Technical Information and Communication – 7,5 credits (Bachelor level, examiner)
- 1DV527 The Web as an Application Platform – 7,5 credits (Bachelor level, Web APIs module)
- 1DT305 Introduction to Applied Internet of Things – 7,5 credits (open level)


My research interests include (but not limited to):

  • Software Engineering (SE)
  • Patterns and Antipatterns in SOAP Web service and RESTful APIs
  • Source Code Analysis and Natural Language Processing
  • Software Maintenance and Evolution
  • Software Architectural Quality
  • Requirements Engineering (RE)
  • Search-based Software Engineering (SBSE)
  • Machine Learning
  • Internet of Things (IoT)


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