ICSME 2023
Sun 1 - Fri 6 October 2023 Bogotá, Colombia
Dates
Wed 4 Oct 2023
Thu 5 Oct 2023
Fri 6 Oct 2023
Tracks
ICSME Artifact Evaluation Track and ROSE Festival
ICSME Industry Track
ICSME Journal First Track
ICSME New Ideas and Emerging Results Track
ICSME Registered Reports Track
ICSME Research Track
ICSME Tool Demo Track
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Wed 4 Oct

Displayed time zone: Bogota, Lima, Quito, Rio Branco change

10:30 - 12:00
Machine Learning ApplicationsResearch Track / Industry Track / New Ideas and Emerging Results Track at Session 1 Room - RGD 004
Chair(s): Masud Rahman Dalhousie University
10:46
16m
Talk
DeltaNN: Assessing the Impact of Computational Environment Parameters on the Performance of Image Recognition Models
Industry Track
Nikolaos Louloudakis University of Edinburgh, Perry Gibson University of Glasgow, José Cano University of Glasgow, Ajitha Rajan University of Edinburgh
13:30 - 15:00
Mining Software RepositoriesResearch Track / New Ideas and Emerging Results Track / Industry Track at Session 1 Room - RGD 004
Chair(s): Denys Poshyvanyk William & Mary, Esteban Parra Belmont University
13:46
16m
Talk
Process Mining from Jira Issues at a Large Company
Industry Track
Bavo Coremans Thermo Fisher Scientific, Arjen Klomp Thermo Fisher Scientific, Satrio Adi Rukmono , Jacob Krüger Eindhoven University of Technology, Dirk Fahland Eindhoven University of Technology, Michel Chaudron Eindhoven University of Technology, The Netherlands

Thu 5 Oct

Displayed time zone: Bogota, Lima, Quito, Rio Branco change

10:30 - 12:00
Software Testing - 1Research Track / Industry Track at Session 1 Room - RGD 004
Chair(s): Amjed Tahir Massey University
11:02
16m
Talk
Software Testing and Code Refactoring: A Survey with Practitioners
Industry Track
Danilo Lima , Ronnie de Souza Santos University of Calgary, Guilherme Pires , Sildemir Silva , César França Federal Rural University of Pernambuco (UFRPE), Luiz Fernando Capretz Western University
10:30 - 12:00
Software ChangesResearch Track / Journal First Track / Industry Track / Tool Demo Track at Session 2 Room - RGD 04
Chair(s): Tushar Sharma Dalhousie University, Shurui Zhou University of Toronto
10:46
16m
Talk
Identifying Defect-Inducing Changes in Visual Code
Industry Track
Kalvin Eng Electronic Arts, Abram Hindle University of Alberta, Alexander Senchenko Electronic Arts
Pre-print
13:30 - 15:00
Security and Program RepairResearch Track / Industry Track at Session 1 Room - RGD 004
Chair(s): Quentin Stiévenart Université du Québec à Montréal (UQAM), Ashkan Sami Edinburgh Napier University
14:02
16m
Talk
Finding an Optimal Set of Static Analyzers To Detect Software Vulnerabilities
Industry Track
Jiaqi He University of Alberta, Revan MacQueen University of Alberta, Natalie Bombardieri University of Alberta, Karim Ali University of Alberta, James Wright University of Alberta, Cristina Cifuentes Oracle Labs
15:30 - 17:00
Software FaultsIndustry Track / Research Track / Journal First Track at Session 1 Room - RGD 004
Chair(s): Masud Rahman Dalhousie University, Ashkan Sami Edinburgh Napier University
15:46
16m
Talk
Predicting Defective Visual Code Changes in a Multi-Language AAA Video Game Project
Industry Track
Kalvin Eng Electronic Arts, Abram Hindle University of Alberta, Alexander Senchenko Electronic Arts
Pre-print
16:18
11m
Talk
Evaluation of Cross-Lingual Bug Localization: Two Industrial Cases
Industry Track
Shinpei Hayashi Tokyo Institute of Technology, Takashi Kobayashi Tokyo Institute of Technology, Tadahisa Kato Hitachi, Ltd.
DOI Pre-print
15:30 - 17:00
Program AnalysisResearch Track / Journal First Track / Industry Track at Session 2 Room - RGD 04
Chair(s): Fabio Petrillo École de technologie supérieure (ÉTS), Montréal -- Université du Québec, Mark Hills Appalachian State University
16:18
11m
Talk
OLA: Property Directed Outer Loop Abstraction for Efficient Verification of Reactive Systems
Industry Track
Priyanka Darke Tata Consultancy Services, Bharti Chimdyalwar Tata Consultancy Services

Fri 6 Oct

Displayed time zone: Bogota, Lima, Quito, Rio Branco change

10:30 - 12:00
10:57
16m
Talk
Cost Reduction on Testing Evolving Cancer Registry System
Industry Track
Erblin Isaku Simula Research Laboratory, and University of Oslo (UiO), Hassan Sartaj Simula Research Laboratory, Christoph Laaber Simula Research Laboratory, Tao Yue Beihang University, Shaukat Ali Simula Research Laboratory and Oslo Metropolitan University, Thomas Schwitalla Cancer Registry of Norway, Jan F. Nygård Cancer Registry of Norway
Pre-print
11:24
16m
Talk
Specification-based Test Case Generation for C++ Engineering Software
Industry Track
13:30 - 14:45
Programming Languages and MigrationNew Ideas and Emerging Results Track / Industry Track / Research Track at Session 1 Room - RGD 004
Chair(s): Esteban Parra Belmont University, Nicolas Archila
13:30
11m
Talk
The Importance of Incremental Migration
Industry Track
13:52
16m
Talk
A Machine Learning Approach to Convert Pseudo-Code to Domain-Specific Programming Language
Industry Track
Jacob Neal Belmont University, Binary Evolution, Shane Rogers Binary Evolution, Esteban Parra Belmont University
14:08
11m
Talk
Parsing Fortran-77 with proprietary extensions
Industry Track
Younoussa Sow DTIPD Framatome, Larisa Safina INRIA Lillle - Nord Europe, Léandre Brault , Papa Ibou Diouf , Stéphane Ducasse Inria; University of Lille; CNRS; Centrale Lille; CRIStAL, Nicolas Anquetil University of Lille, Lille, France
13:30 - 14:45
13:57
16m
Talk
A Case Study of DevOps Adoption within a Large Financial Organisation
Industry Track
Lixin Su Barclays Bank UK, Tim Storer University of Glasgow

Accepted Papers

Title
A Case Study of DevOps Adoption within a Large Financial Organisation
Industry Track
A Machine Learning Approach to Convert Pseudo-Code to Domain-Specific Programming Language
Industry Track
Cost Reduction on Testing Evolving Cancer Registry System
Industry Track
Pre-print
DeltaNN: Assessing the Impact of Computational Environment Parameters on the Performance of Image Recognition Models
Industry Track
Evaluation of Cross-Lingual Bug Localization: Two Industrial Cases
Industry Track
DOI Pre-print
Finding an Optimal Set of Static Analyzers To Detect Software Vulnerabilities
Industry Track
Identifying Defect-Inducing Changes in Visual Code
Industry Track
Pre-print
OLA: Property Directed Outer Loop Abstraction for Efficient Verification of Reactive Systems
Industry Track
Parsing Fortran-77 with proprietary extensions
Industry Track
Predicting Defective Visual Code Changes in a Multi-Language AAA Video Game Project
Industry Track
Pre-print
Process Mining from Jira Issues at a Large Company
Industry Track
Software Testing and Code Refactoring: A Survey with Practitioners
Industry Track
Specification-based Test Case Generation for C++ Engineering Software
Industry Track
The Importance of Incremental Migration
Industry Track

Call for Papers

Goal and Scope

The industry track brings together participants from academia and industry in a venue that highlights practical and real-world studies of software maintenance and evolution. This track aims to foster mutually-beneficial links between those engaged in scientific research and practitioners working to improve software maintenance and evolution practices. Experiences from practitioners provide crucial input into future research directions and allow others to learn from successes and failures.

The ICSME 2023 industry track highlights practical and real-world studies of software maintenance and evolution. Submissions to this track should address:

  • Real-world success and/or failure stories and evidence evolving and maintaining systems
  • Experiences and lessons applying state-of-the-art methods, techniques, and tools to industrial software evolution and maintenance problems
  • New and unsolved challenges derived from practical problems

We are interested in results, obstacles, and lessons learned. If you apply in an industrial context a method, technique, or tool that was previously presented at ICSME or another software engineering conference, we greatly encourage you to submit to this track. In addition, machine learning models have now become essential to an intelligent software system. Papers reporting experiences and tools on the maintenance and evolution of machine learning models in a software system are also welcomed.

Submission Types

We invite submissions of state-of-the-art practice and experience reports, survey reports from real-world projects and industrial experiences, and evidence-based identification of unsolved research challenges associated with software maintenance and evolution. Each submission should describe the problem addressed, the approach used, the current state of the project, an evaluation of the benefits or lessons learned, and future developments. Submissions may be extended abstracts to encourage discussion around a specific topic or open question (1 page), short papers (4 pages), or long papers (10 pages). We particularly encourage short papers that might get extended into further work, once their novelty has been acknowledged.

Extended abstracts (1 page) may address:

  • Important industry needs that are not adequately addressed in the research community
  • Ways to improve communication between the research and practitioner communities
  • Ways to make research papers more accessible to industry
  • New and unsolved research challenges derived from practical problems
  • Success stories reporting benefits and lessons learned
  • Failure stories reporting obstacles and lessons learned

Short papers (4 pages) may address:

  • New and unsolved research challenges derived from practical problems
  • Success stories reporting benefits and lessons learned
  • Failure stories reporting obstacles and lessons learned
  • State-of-the-practice and experience reports with empirical evidence
  • State-of-the-practice surveys reports from real-world projects
  • Application reports about methods, techniques, and tools

Long papers (10 pages) may include:

  • State-of-the-practice and experience reports with empirical evidences
  • State-of-the-practice surveys reports from real-world projects
  • In-depth application reports about methods, techniques, and tools
  • We welcome submissions that are mainly driven by practitioners as much as submissions that are mainly driven by researchers!

Researcher-driven submissions:

A paper is considered researcher-driven if the main author(s) are researchers (the paper can have industrial co-authors). Researcher-driven submissions to the industry track should be distinguished from research track submissions by richness in industrial data or their focus on industrial cases.

Practitioner-driven submissions:

A paper is considered practitioner-driven if the main author(s) are practitioners (the paper can have co-authors from academia). These papers may focus more on specific cases or applications and do not require the same degree of generalizability as researcher-driven submissions.

Reviews

Submissions will be reviewed by at least three members of the industry track program committee. The committee consists of 50-70% practitioners or industrial researchers, who have a good understanding of the value of industry contributions and collaborations. The evaluation serves the purpose to ensure the quality of the submissions and provide constructive feedback. Papers that successfully pass the review process will be accepted for presentation and publication. The type of the paper (researcher-driven or practitioner-driven) will be considered during the review. The below criteria will be considered by the reviewers:

Relevance to ICSME audience: The core concepts of the work either originate in research, or are novel ICSME-appropriate topics related to software maintenance and evolution.

Improvement on the state-of-the-practice or state-of-knowledge: The amount of improvement that the work achieves above and beyond the state-of-the-practice (demonstrated with evidence from practice) or the scale of the impact (e.g., individual vs team vs several teams) of the tech transfer work demonstrated with evidence from practice. Extended Abstract papers should indeed cover a practical problem that practitioners are facing and that our research community might either not be aware of, or where our research hasn’t trickled down into a usable (or known) tool so that practitioners can use it.

Generality of results (researcher-driven papers): The probability that the work, approach, or lessons learned are applicable to developers outside of the studied group.

Clarity of lessons learned: The clarity in which the lessons learned are presented and how well they are supported with data and discussion.

Overall quality of the manuscript: Submissions that are not in compliance with the required submission format or that are out of the scope of the conference will be rejected without being reviewed. Submitted papers must comply with IEEE plagiarism policy and procedures. Papers submitted to the industry track must not have been published elsewhere and must not be under review or submitted for review elsewhere while under consideration for ICSME 2023.

Publication and Presentation

Accepted papers will be published in the IEEE Xplore Digital Library. Please review the ICSME 2023 Publication Requirements for more details. Presentation details will follow notifications of acceptance.

How to Submit

For 2023, we will follow a single-anonymous review process (i.e., reviewers can see author names and affiliations). A single-anonymous review process should enable authors to fully describe their context and case studies, which are core in industry-track papers. Submitted papers must adhere to the following rules:

  • Author names and affiliations should appear on the paper.
  • References to authors’ own related work should be made explicit.
  • Submissions must strictly adhere to the two-column IEEE conference proceedings format. You can find the templates here. LaTeX users should use the following configuration: \documentclass[conference]{IEEEtran}. Microsoft Word users should use the US Letter format template. Papers must not exceed 1 page (for extended abstracts), 4 pages (for short papers) or 10 pages (for long papers), including all text, references, figures, and appendices.
  • All submissions must be in PDF and must be submitted online by the deadline via the ICSME 2023 EasyChair conference management system
  • All authors, reviewers, and organizers are expected to uphold the IEEE Code of Conduct.

Submission Link

Please use the following link: https://easychair.org/my/conference?conf=icsme2023

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