ESEM Registered ReportsESEIW 2023

ESEM 2023 - Registered Reports Track

Call for Registrations

Empirical Software Engineering journal (EMSE), in conjunction with the ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM), is continuing the RR track. The RR track of ESEM 2023 has two goals: (1) to prevent HARKing (hypothesizing after the results are known) for empirical studies; (2) to provide early feedback to authors on their initial study design. For papers submitted to the RR track, methods and proposed analyses are reviewed prior to execution. Pre-registered studies follow a two-step process:

• Stage 1: A report is submitted that describes the planned study. The submitted report is evaluated by the reviewers of the RR track of ESEM 2023. Authors of accepted pre-registered studies will be given the opportunity to present their work at ESEM.
• Stage 2: Once a report has passed Phase 1, the study will be conducted, and actual data collection and analysis take place. The results may also be negative! The full paper is submitted for review to EMSE journal.

See the associated Author’s Guide. Please contact the ESEM track chairs – Michael Federer or Fabio Silva – for any questions, clarifications, or comments.

Paper Types, Evaluation Criteria, and Acceptance Types

The RR track of ESEM 2023 supports two types of papers:

Confirmatory: The researcher has a fixed hypothesis (or several fixed hypotheses) and the objective of the study is to find out whether the hypothesis is supported by the facts/data.

An example of a completed confirmatory study:

• Davide Fucci, Giuseppe Scanniello, Simone Romano, Martin Shepperd, Boyce Sigweni, Fernando Uyaguari, Burak Turhan, Natalia Juristo, and Markku Oivo. An External Replication on the Effects of Test-driven Development Using a Multi-site Blind Analysis Approach. In Proceedings of the 10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM ’16). Association for Computing Machinery, New York, NY, USA, Article 3, 1–10. https://doi.org/10.1145/2961111.2962592
• Inozemtseva, L., & Holmes, R. (2014, May). Coverage is not strongly correlated with test suite effectiveness. In Proceedings of the 36th international conference on software engineering (pp. 435-445).

Exploratory: The researcher does not have a hypothesis (or has one that may change during the study). Often, the objective of such a study is to understand what is observed and answer questions such as WHY, HOW, WHAT, WHO, or WHEN. We include in this category registrations for which the researcher has an initial proposed solution for an automated approach (e.g., a new deep-learning-based defect prediction approach) that serves as a starting point for his/her exploration to reach an effective solution.

Examples of completed exploratory studies:

• Danilo Caivano, Pietro Cassieri, Simone Romano, and Giuseppe Scanniello. An Exploratory Study on Dead Methods in Open-source Java Desktop Applications. In Proceedings of the 15th ACM / IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM) (ESEM ’21). Association for Computing Machinery, New York, NY, USA, Article 10, 1–11. https://doi.org/10.1145/3475716.3475773
• Gousios, G., Pinzger, M., & Deursen, A. V. (2014, May). An exploratory study of the pull-based software development model. In Proceedings of the 36th International Conference on Software Engineering (pp. 345-355).

The reviewers will evaluate RR track submissions based on the following criteria:

• The importance of the research question(s).
• The logic, rationale, and plausibility of the proposed hypotheses.
• The soundness and feasibility of the methodology and analysis pipeline (including statistical power analysis where appropriate).
• (For confirmatory study) Whether the clarity and degree of methodological detail is sufficient to exactly replicate the proposed experimental procedures and analysis pipeline.
• (For confirmatory study) Whether the authors have pre-specified sufficient outcome-neutral tests for ensuring that the results obtained can test the stated hypotheses, including positive controls and quality checks.
• (For exploratory study, if applicable) The description of the data set that is the base for exploration.

The outcome of the RR report review is one of the following:

• In-Principal Acceptance (IPA): The reviewers agree that the study is relevant, the outcome of the study (whether confirmation / rejection of hypothesis) is of interest to the community, the protocol for data collection is sound, and that the analysis methods are adequate. The authors can engage in the actual study for Stage 2. If the protocol is adhered to (or deviations are thoroughly justified), the study is published. Of course, this being a journal submission, a revision of the submitted manuscript may be necessary. Reviewers will especially evaluate how precisely the protocol of the accepted pre-registered report is followed, or whether deviations are justified.
• Continuity Acceptance (CA): The reviewers agree that the study is relevant, that the (initial) methods appear to be appropriate. However, for exploratory studies, implementation details and post-experiment analyses or discussion (e.g., why the proposed automated approach does not work) may require follow-up checks. We’ll try our best to get the original reviewers. All PC members will be invited on the condition that they agree to review papers in both, Stage 1 and Stage 2. Four (4) PC members will review the Stage 1 submission, and three (3) will review the Stage 2 submission.
• Rejection: The reviewers do not agree on the relevance of the study or are not convinced that the study design is sufficiently mature. Comments are provided to the authors to improve the study design before starting it.

Note: For ESEM 2023, we will only offer IPA to confirmatory studies. Exploratory studies in software engineering often cannot be adequately assessed until after the study has been completed and the findings are elaborated and discussed in a full paper. For example, consider a study in an RR proposing defect prediction using a new deep learning architecture. This work falls under the exploratory category. It is difficult to offer IPA, as we do not know whether it is any better than a traditional approach based on e.g., decision trees. Negative results are welcome; however, it is important that the negative results paper goes beyond presenting “we tried and failed”, but rather provides interesting insights to readers, e.g., why the results are negative or what that means for further studies on this topic. Furthermore, it is important to note that authors are required to document all deviations (if any) in a section of the paper.

Submission Process and Instructions

The timeline for ESEM 2023 RR track will be as follows:

May 30: Authors submit their initial report.

• Submissions must not exceed 6 pages (plus 1 additional page of references). The page limit is strict.
• Submissions must conform to the IEEE conference proceedings template, specified in the IEEE Conference Proceedings Formatting Guidelines (title in 24pt font and full text in 10pt type, LaTeX users must use \documentclass[10pt,conference]{IEEEtran} without including the compsoc or compsocconf options).

June 1: Authors receive PC members’ reviews.

June 15: Authors submit a response letter + revised report in a single PDF.

• The response letter should address reviewer comments and questions.
• The response letter + revised report must not exceed 12 pages (plus 1 additional page of references).
• The response letter does not need to follow IEEE formatting instructions.

June 21: Notification of Stage 1

• (Outcome: in-principal acceptance, continuity acceptance, or rejection).

August 28 Authors submit their accepted RR report to arXiv

• To be checked by PC members for Stage 2
• Note: Due to the timeline, RR reports will not be published in the ESEM 2023 proceedings. Authors will present their RR during the conference

Before May 02, 2024: Authors submit a full paper to EMSE Journal. Instructions will be provided later. However, the following constraints will be enforced:

• Justifications need to be given to any change of authors. If the authors are added/removed or the author order is changed between the original Stage 1 and the EMSE journal submission, all authors will need to complete and sign a “Change of authorship request form”. The Editors in Chief of EMSE and chairs of the RR track reserve the right to deny author changes. If you anticipate any authorship changes, please reach out to the chairs of the RR track as early as possible.
• PC members who reviewed an RR report in Stage 1 and their directly supervised students cannot be added as authors of the corresponding submission in Stage 2.

Submissions can be made via the submission site https://easychair.org/my/conference?conf=esem2023 by the submission deadline. Any submission that does not comply with the aforementioned instructions and the mandatory information specified in the Author Guide is likely to be desk rejected. In addition, by submitting, the authors acknowledge that they are aware of and agree to be bound by the following policies:

• The IEEE Plagiarism FAQ. Papers submitted to ESEM 2023 must not have been published elsewhere and must not be under review or submitted for review elsewhere whilst under consideration for ESEM 2023. Contravention of this concurrent submission policy will be deemed a serious breach of scientific ethics, and appropriate action will be taken in all such cases (including immediate rejection and reporting of the incident to IEEE). To check for double submission and plagiarism issues, the chairs reserve the right to (1) share the list of submissions with the PC Chairs of other conferences with overlapping review periods and (2) use external plagiarism detection software, under contract to IEEE, to detect violations of these policies.

• The authorship policy of the IEEE

Author’s Guide 

NB: Please contact the ESEM RR track chairs with any questions, feedback, or requests for clarification. Specific analysis approaches mentioned below are intended as examples, not mandatory components.

I. Title (required)

Provide the working title of your study. It may be the same title that you submit for publication of your final manuscript, but it is not mandatory. Example: Should your family travel with you on the enterprise? Subtitle (optional): Effect of accompanying families on the work habits of crew members

II. Authors (required)

At this stage, we believe that a single blind review is most productive.

III. Structured Abstract (required)

The abstract should describe the following in 200 words or so:

• Background/Context
  What is your research about? Why are you doing this research, why is it interesting? Example: “The enterprise is the flag ship of the federation, and it allows families to travel onboard. However, there are no studies that evaluate how this affects the crew members.”

• Objective/Aim
  What exactly are you studying/investigating/evaluating? What are the objects of the study? We welcome both confirmatory and exploratory types of studies.

  • Example (Confirmatory): We evaluate whether the frequency of sick days, the work effectiveness and efficiency differ between science officers who bring their family with them, compared to science officers who are serving without their family.
  • Example (Exploratory): We investigate the problem of frequent Holodeck use on interpersonal relationships with an ethnographic study using participant observation, in order to derive specific hypotheses about Holodeck usage.

• Method
  How are you addressing your objective? What data sources are you using?

  • Example: We conduct an observational study and use a between subject design. To analyze the data, we use a t-test or Wilcoxon test, depending on the underlying distribution. Our data comes from computer monitoring of Enterprise crew members.

IV. Introduction

Give more details on the bigger picture of your study and how it contributes to this bigger picture. An important component of phase 1 review is assessing the importance and relevance of the study questions, so be sure to explain this.

V. Hypotheses (required for confirmatory study) or research questions

Clearly state the research hypotheses that you want to test with your study, and a rationalization for the hypotheses. Hypothesis: Science officers with their family on board have more sick days than science officers without their family Rationale: Since toddlers are often sick, we can expect that crew members with their family onboard need to take sick days more often.

VI. Variables (required for confirmatory study)

• Independent Variable(s) and their operationalization
• Dependent Variable(s) and their operationalization (e.g., time to solve a specified task)
• Confounding Variable(s) and how their effect will be controlled (e.g., species type (Vulcan, Human, Tribble) might be a confounding factor; we control for it by separating our sample additionally into Human/Non-Human and using an ANOVA (normal distribution) or Friedman (non-normal distribution) to distill its effect).

For each variable, you should give:

• name (e.g., presence of family)
• abbreviation (if you intend to use one)
• description (whether the family of the crew members travels on board)
• scale type (nominal: either the family is present or not)
• operationalization (crew members without family on board vs. crew members with family onboard)

VII. Participants/Subjects/Datasets (required)

Describe how and why you select the sample. When you conduct a meta-analysis, describe the primary studies / work on which you base your meta-analysis.

Example: We recruit crew members from the science department on a voluntary basis. They are our targeted population.

VIII. Execution Plan (required)

Describe the experimental setting and procedure. This includes the methods/tools that you plan to use (be specific on whether you developed it (and how) or whether it is already defined), and the concrete steps that you plan to take to support/reject the hypotheses or answer the research questions.

Example: Each crew member needs to sign the informed consent and agreement to process their data according to GDPR. Then, we conduct the interviews. Afterwards, participants need to complete the simulated task …

Accepted Papers