|
SCOPE AND OBJECTIVES
This workshop focuses on increasing our understanding of the nature of Software Qualities (SQs), ilities, or extra-functional requirements (reliability, usability, affordability, etc.), and their interrelationships, and of bringing them into balance in the practice of software engineering. The relevance and timeliness of this topic reflects the current and future trends toward more software-intensive systems, with greater complexity, autonomy, speed of change, and need for interoperability within systems of systems, given the frequent system shortfalls and overruns that occur when their SQ balance is not achieved. Some good research and practices are becoming available, but there is overall chaos among SQ practices, definitions, standards and relationships. The workshop aims to bring together SQ researchers and practitioners to help create more solid foundations for dealing with SQs.
---------------------------------------------------------------------------
AREAS OF INTERESTS
The following are five primary areas of interest for the Workshop:
* SQs in practice: Experience reports, lessons learned, case-studies, benchmarks, experiments, negative results due to unknown dependencies, best practices and success stories.
*Specification and modelling notations of SQs These include but are not limited to: a specific property (cost, performance, resource consumption, reliability, security, etc.), set of properties, traceability during the development process, traceability over the software lifecycle, model annotations.
* SQs validation and verification These take the dependencies into consideration: measurements, evaluation methods, trade-off analysis, formal methods, multi-criteria analysis, testing, simulation of a given property or set of properties.
* SQs Data Analytics and Machine Learning Significant progress is being made in large-scale analysis of a software system’s code smells, technical debt, vulnerabilities, and architecture deficiencies across a software system’s commit history. Further research is underway in exploring such machine learning approaches as learning predictive models, transfer learning, uncertainty in models, continuous verification, deep learning, model optimization, and self-adaptation.
* State-of-the-art and ontological dependencies Dependencies can be to different parameters involved in the assessment of the properties, or dependencies to other properties and include synergies, conflicts, means-ends relations, quantitative tradespace models, and SQ variation by system state, process, stakeholder value propositions, and operational context.
* Contributions from other SQ-relevant topics are welcome as well.
---------------------------------------------------------------------------
SUBMISSION GUIDELINES
SQUADE welcomes three types of contributions to enable works in different research phases to be discussed at the workshop:
* Long papers (max. 8 pages including figures, appendices and references) This category gathers papers which provide novel contributions, papers which address challenging problems with innovative idea, experience reports and case-studies focusing on the dependencies of software qualities in software engineering. Long papers should clearly describe the context of the work or the problem that is addressed, the relevant state-of-the-art, the contribution and discuss the advantages and shortcoming of the proposed contribution. Long papers will be evaluated with respect to the clarity of the presentation, the relevance to the workshop, the originality of the idea and the soundness of the contribution.
* Short papers (max. 4 pages including figures, appendices and references) This category includes new ideas, vision and position papers, research preview, tool demonstrations, early results, benchmark examples and any other work in early stages which might not have been fully validated yet. Short papers will be evaluated with respect to the clarity, relevance, interest for the workshop and the potential for fruitful discussions.
* Industry experience reports (max. 2 pages including figures, appendices and references). This category targets practitioners to share their experience with software qualities and their dependencies (positive and negative experience reports, lessons learned, success stories, etc.). Industry experience reports will be evaluated with respect to the interest for the workshop and the potential for fruitful discussions.
The papers submitted to SQUADE must be original (i.e., not published or submitted elsewhere) and follow the ESEC/FSE formatting guidelines. Accepted papers will be published in the ESEC/FSE workshop proceedings and published in the ACM Digital Library prior to the event. The official publication date of the workshop proceedings is the date the proceedings are made available in the ACM Library. This date may be up to two weeks prior to the first day of ESEC/FSE 2019. The official publication date affects the deadline for any patent filings related to published work. Submission is done through Easy Chair at https://easychair.org/conferences/?conf=squade19
---------------------------------------------------------------------------
PROGRAM ORGANIZERS
Dr. Séverine Sentilles, Mälardalen University, Sweden [email protected]
Prof. Barry Boehm, University of Southern California, USA [email protected]
Dr. Catia Trubiani,L'Aquila, Italy [email protected]
Jun.-Prof. Dr.-Ing Anne Koziolek Karlsruhe Institute of Technology,Karlsruhe, Germany [email protected]
---------------------------------------------------------------------------
PROGRAM COMMITTEE
The following list represents the tentative program committee.
Aldeida Aleti, Monash University, Australia
Jean-Michel Bruel, Toulouse University, France
Jan Carlson, Mälardalen University, Sweden
Celia Chen, USC, USA
Sunita Chulani, Cisco, USA
Federico Ciccozzi, Mälardalen University, Sweden
Laurence Duchien, Lille University, France
Xavier Franch, Universitat Politecnica Catalunya, Spain
Marcela Genero, U. Castilla La Mancha, Spain
Robert Heinrich, Karlsruhe Inst. of Technology, Germany
Pooyan Jamshidi, Carnegie Mellon U, USA
Andreas Jedlitchska, Fraunhofer IESE, Germany
Daniel Mendez-Fernandez, Technical University Munich, Germany
Zhen Ming (Jack) Jiang, York University, Canada
Cristina Palomares, Universitat Politècnica de Catalunya, Spain
Efi Papatheocharous, Rise SICS, Sweden
Dorina Petriu, Carleton University, Canada
Guenther Ruhe, U. Calgary, Canada
Bernhard Rumpe, RWTH Aachen University
Mehrdad Saadatmand, Rise SICS, Sweden
Rick Selby, Northrop Grumman Corporation, USA
Guilherme Travassos, Federal University of Rio de Janeiro, Brazil
Andre van Hoorn, University of Stuttgart, Germany
Aneta Vulgarakis Feljan, Ericsson Research, Sweden
Qing Wang, ISCAS, China
|
