APSEC 2023
Mon 4 - Thu 7 December 2023 Seoul, South Korea

Call for Papers: Technical Track

The APSEC 2023 technical research track invites high-quality contributions describing original results in the discipline of software engineering. Solicited topics include, but are not limited to:

  • Tools and processes
    • Agile processes
    • DevOps and Container
    • Configuration Management and Deployment
    • Software Engineering Process and Standards
  • Requirements and Design
    • Service-oriented Computing
    • Component-based Software Engineering
    • Cooperative, Distributed, and Global Software Engineering
    • Software Architecture, Modeling and Design
    • Middleware, Frameworks, and APIs
    • Software Product-line Engineering
  • Testing and Analysis
    • Testing, Verification, and Validation
    • Program Analysis
    • Program Synthesis
    • Program Repairs
  • Formal Aspects of Software Engineering
    • Formal Methods
    • Model-driven and Domain-specific Engineering
  • Human Factors and Social Aspects of Software Engineering
    • Software Comprehension, Visualization, and Traceability
    • Software for Green and Sustainable Technologies
  • AI and Software Engineering
    • Search-based Software Engineering
    • AI for SE, SE for AI
  • Dependability, Safety, and Reliability
  • Software Maintenance and Evolution
    • Refactoring
    • Reverse Engineering
    • Software Reuse
    • Software Project Management
    • Debugging, Defect Prediction and Fault Localization
  • Software Repository Mining and Data Analytics

APSEC2023 welcomes submissions addressing topics in a variety of application domains, including mobile, cloud, blockchains, embedded and cyber-physical systems.

Evaluation Criteria

Technical research papers must not be more than 10 pages (including references). Submissions will be evaluated by at least three program committee members. The evaluation will focus on the novelty, originality, importance to the field, proper use of research methods, and presentation of the submissions.

Submission Instructions

Submitted papers must have been neither previously accepted for publication nor concurrently submitted for review in another journal, book, conference, or workshop.

All submissions must be in English and must come in A4 paper size PDF format and conform, at the time of submission, to the IEEE Conference Proceedings Formatting Guidelines (title in 24pt font and full text in 10pt font, LaTeX users must use \documentclass[10pt,conference]{IEEEtran} without including the compsoc or compsocconf option). Also, papers must comply with the IEEE Policy on Authorship. Submissions must be submitted electronically in PDF before the due date via EasyChair.

The Chairs reserve the right to reject submissions (without reviews) that are not in compliance or out of scope for the conference.

IMPORTANT: The APSEC 2023 technical research track will use a double-blind reviewing process, which means that submissions must not reveal the authors’ identities. The authors must make every effort to honor the double-blind reviewing process. Submissions must adhere to the following rules (largely reused from ASE 2017 double-blind instructions and SANER 2022 double-blind instructions). Please read carefully the APSEC 2023 double-blind instructions before preparing your paper.

Submission Link

Papers must be submitted through https://easychair.org/conferences/?conf=apsec2023

Important Dates

  • Abstract Deadline: June 30, 2023 July 7, 2023
  • Paper Deadline: July 7, 2023 July 14, 2023
  • Author Notification: Aug 18, 2023 Aug 23, 2023
  • Camera Ready Deadline: Oct 13, 2023 Oct 20, 2023

Accepted Papers and Attendance Expectation

All accepted papers will be submitted to the CS Digital Library as the APSEC 2023 conference proceedings.

Accepted papers will not be permitted any additional page of content. But, we hope that the authors will reflect the reviewers’ comments as much as possible in the camera-ready version. After acceptance, the list of paper authors can not be changed under any circumstances, and the list of authors on camera-ready papers must be identical to those on submitted papers. After acceptance, paper titles can not be changed except by permission of the Program Co-Chairs, and only then when referees recommend a change for clarity or accuracy with paper content. If a submission is accepted, at least one author of the paper must register for APSEC 2023 and present the paper at the conference. If an accepted paper is not presented, the paper is removed from the proceedings.


Yunja Choi and Meng Yan
APSEC 2023 Program Co-Chairs

IMPORTANT: The APSEC 2023 technical research track will use a double-blind reviewing process, which means that submissions must not reveal the authors’ identities. The authors must make every effort to honor the double-blind reviewing process. Submissions must adhere to the following rules (largely reused from SANER 2022 double-blind instructions).

  • Omit authors’ names and institutions from your title page.
  • References to authors’ own related work must be in the third person. (For example, not “We build on our previous work…” but rather “We build on the work of…”)
  • There may be cases in which the current submission is a clear follow up of one of your previous work, and despite what recommended in the previous point, reviewers will clearly associate authorship of such a previous work to the current submission. In this case, you may decide to anonymize the reference itself at submission time. For example: “based on previous results [10]” .. where the reference is reported as “[10] Anonymous Authors. Omitted for double blind reviewing.” In doing so, however, please make sure that the APSEC 2023 submission is self-contained and its content can be reviewed and understood without accessing the previous paper.
  • Do not include acknowledgements of people, grants, organizations, etc. that would give away your identity. You may, of course, add these acknowledgements in the camera-ready version.
  • In general, aim to reduce the risk of accidental unblinding. For example, if you use an identifiable naming convention for your work, such as a project name, use a different name for your submission, which you may indicate has been changed for the purposes of double-blind reviewing. This includes names that may unblind individual authors and their institutions. For example, if your project is called GoogleDeveloperHelper, which makes it clear the work was done at Google, for the submission version, use the name DeveloperHelper or BigCompanyDeveloperHelper instead.
  • Avoid revealing the institution affiliations of authors or at which the work was performed. For example, if the evaluation includes a user study conducted with undergraduates from the CS 101 class that you teach, you might say “The study participants consist of 200 students in an introductory CS course.” You can of course add the institutional information in the camera-ready. Similar suggestions apply for work conducted in specific organizations (e.g., industrial studies). In such cases, avoid mentioning the organization’s name. Instead, you may just refer to the organization as “Org” or “Company”, etc. When appropriate and when this does not help too much in revealing the company’s name, you might mention the context (e.g., financial organization, video game development company, etc.).
  • APSEC 2023 believes in open science and that open science aids reproducibility and replicability. To improve these factors we encourage authors to consider disclosing the source code and datasets used within their paper, including extractors, survey data, etc. By sharing this information your contribution will be more impactful because others can follow up on your work and of course cite it. But please avoid linking directly to code repositories or tool deployments which can reveal your identity. Instead of doing so, please consider using Zenodo, Figshare, or other services that provide DOIs and allowing anonymous and semi-anonymous methods of archiving software and datasets. Archive.org is recommended for the dissemination of larger datasets. These datasets, anonymized through Zenodo and other services, should be linked within the paper itself. Instructions for double-blind friendly uploading of datasets is available here: https://ineed.coffee/post/how-to-disclose-data-for-double-blind-review-and-make-it-archived-open-data-upon-acceptance.html