About ISE'22

The Second Brazilian Workshop on Intelligent Software Engineering (ISE'22) will be held in a virtual form. ISE'22 is is co-located with the 13th Brazilian Conference on Software: Theory and Practice (CBSoft 2022).

Aims and Scope

In modern society, software is ubiquitous, being present in almost every aspect of life. However, developing software is costly. Therefore, there is a continuous effort for innovative designs for helping make software more reliable, maintainable, and reduce its development cost. Further, there is an increase of AI-enabled software, bringing new software engineering challenges.

In recent years, Intelligent Software Engineering (ISE) has emerged as a promising means to address these challenges. ISE is ambidextrous, including solutions based on (i) applying Intelligent Techniques to Software Engineering problems, but also on (ii) applying Software Engineering to developing Intelligent Systems.

An Intelligent Technique is defined as a technique that explores data (from digital artifacts or domain experts) for knowledge discovery, reasoning, learning, planning, natural language processing, perception, or supporting decision-making. Examples of Intelligent Techniques are search and optimization (e.g., genetic algorithm), machine learning, deep learning, data mining, recommender systems, reasoning under uncertainty (e.g., Bayesian networks), software analytics, and decision analysis. An intelligent system is a system that applies an Intelligent Technique for a given domain, such as a product recommender.

The goal of ISE’22 is to strengthen the Intelligent Software Engineering community by integrating researchers and professionals from different areas (Software Engineering, Artificial Intelligence, Analytics, etc) to discuss and advance the state of the art and practice of ISE, its use, and application in the industry.

Topics that are within the scope of this workshop include (but are not limited to):

Submission Guidelines

Paper Format

ISE accepts papers in two formats.

Technical Papers (6 pages)

ISE accepts papers within the context of Intelligent Software Engineering. Both positive and negative results are welcome, though negative results should still be based on rigorous research and provide details on lessons learned.

Industry papers (2-4 pages)

Results, challenges, lessons learned from industrial applications of Intelligent Software Engineering.

Instruction for Authors

Papers can be submitted in Portuguese or English. Submission in English is strongly encouraged. The acceptance of a paper implies that at least one of its authors will register at CBSoft 2022 to present it. All submissions must be in Adobe Portable Document Format (PDF) and must comply with the ACM 2-column conference format (ACM_SigConf) available at this link. LaTeX users must use the acmart.cls class provided in the template with the conference format enabled at the document preamble: \documentclass[sigconf]{acmart}

Authors must use the ACM-Reference-Format.bst bibliography style also provided in the template: \bibliographystyle{ACM-Reference-Format}

Submissions must be no longer than the limits defined in the Paper Format section, including all figures and references.

Papers should be electronically submitted through JEMS. Submissions that are not in compliance with the required submission format, are out of the scope of the symposium, or were submitted or published in any other forum (conference or journal) will be rejected without review. All other papers will be reviewed by at least three Program Committee members.

We strongly encourage authors to submit their tools and data to Zenodo, which adheres to FAIR (findable, accessible, interoperable, and re-usable) principles and provides DOI versioning.

Double-Blind Submission

ISE’2022 will follow a double-blind review process. All submitted papers should conceal the identity of the authors. Both author names and affiliations must be omitted. In addition, the following rules should be addressed:

After the paper acceptance, all the paper information (without anonymization) can be included in the camera-ready version.

Any questions about the preparation of the paper following the double-blind rules can be sent to the Program Committee Chairs.

Organization, Chairs and Important Dates

Organization:

ISE is a workshop organized and promoted by USP and Insper, and supported by VIRTUS/UFCG (virtus.ufcg.edu.br).

Chairs:

Alfredo Goldman (gold@usp.edu.br)

Graziela Simone Tonin (grazielast@insper.edu.br)

Important Dates:

Keynote

Person keynote picture profile

Damian Andrew Tamburri

Associate Professor at TU/e - JADS

Short Bio:

Damian is an Associate Professor at the Eindhoven Univ. of Technology and Jheronimus Academy of Data Science, in s'Hertogenbosch, The Netherlands. Damian completed his Ph.D. at VU University Amsterdam, The Netherlands in March 2014 "with mention" one year in advance of a standard Ph.D. Contract. His research interests lie mainly in Complex Software and Data Architectures (with a focus on Data-Intensive Architectures, Cloud & Microservices as well as Machine-Learning & Computational Intelligence Architectures), Complex Software Architecture Properties (with a focus on Privacy & Security), and Empirical Software Engineering (with a focus on Organisational, Social, and Societal aspects with Qualitative Methods, social-networks analysis as well as Machine-Learning). Damian has published over 100+ papers in either Journals such as the Transactions on Software Engineering (TSE) Journal, The ACM Computing Surveys (CSUR) Journal, the IEEE Software Magazine or top software engineering conferences (such as ICSE or FSE) and top software architecture conferences (such as ECSA or WICSA). Also, Damian is an active contributor and lead research in many EU FP6, FP7, and H2020 projects, such as S-Cube, MODAClouds, SeaClouds, DICE, ANITA, DossierCLOUD, ProTECT, RADON, SODALITE, and more. In addition, Damian is IEEE Software and ACM TOSEM editorial board member, secretary of the TOSCA TC as well as secretary of the IFIP TC2, TC6, and TC8 WG on “Service-Oriented Computing”.

Person keynote picture profile

Danilo Sato

Head of data & AI Services UK and Europe

Short Bio:

As the Data service line lead for Thoughtworks, Danilo is responsible for building high-performing teams to solve our client’s most complex data problems. He leads technical projects in many areas of architecture and engineering, including software, data, infrastructure, and machine learning.

As an acknowledged thought-leader in the data space, Danilo has published books such as Devops in Practice, and has spoken at conferences around the world on data architecture and machine learning.

As an acknowledged thought-leader in the data space, Danilo has published books such as Devops in Practice, and has spoken at conferences around the world on data architecture and machine learning.

Best Paper Award

The authors of the best paper award will receive a special gift.

Program Committee

TBD

Program

TBD