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2019-11-07

Scope


The technical track of MSR 2020 solicits novel, high quality submissions on a wide range of topics, including (but not limited to):


Analysis of software data with the goal of improving software productivity and reliability

Analysis and modeling of runtime information to optimize deployment, delivery and error handling in software development processes

Analysis of change patterns and trends to assist in future development

Analysis of natural language artifacts in software data

Analysis of software ecosystems and mining of software data across multiple projects

Approaches, applications, and tools for mining software data

Artificial intelligence for software engineering

Characterization, classification, and prediction of software defects based on analysis of software data

Characterization of bias in mining and guidelines to ensure the quality of results

Data science for software projects

Empirical studies on extracting data from large long-lived and/or industrial projects

Machine learning for software engineering

Meta-models, exchange formats, and infrastructure tools to facilitate the sharing of extracted data and to encourage reuse and repeatability

Methods of integrating mined data from various historical sources

Mining code review data

Mining execution traces and logs

Mining human and social aspects of development

Mining interaction data

Mining mobile app stores and app reviews

Mining software licensing and copyrights

Models for social and development processes in large software projects

Models of software project evolution based on historical repository data

Models and processes for improving the quality of machine learning pipelines

Natural language processing in software engineering

Prediction and modeling of software quality

Privacy and ethics in mining software data

Release engineering, including continuous integration, delivery and deployment

Search-driven software development, including search techniques to assist developers in finding suitable components and code fragments for reuse, and software search engines

Software analytics

Software engineering for artificial intelligence and machine learning

Energy efficiency of software

Studies of programming language features and their usage

Techniques and tools for capturing new forms of software data such as effort data, fine-grained changes, and refactoring

Techniques to model reliability and defect occurrences

Visualization techniques and models of mined data


Types of Technical Track Submissions


We accept both full (10 pages plus 2 additional pages of references) and short (4 pages plus 1 additional page of references) papers. Furthermore, in order to facilitate the reviewing process of your paper’s contribution, you should select one of the following paper categories:


1. Research Paper


Full research papers are expected to describe new methodologies and/or provide novel research results, and should be evaluated scientifically. While a high degree of technical rigor is expected for long papers, short research papers should discuss controversial issues in the field, or describe interesting or thought-provoking ideas that are not yet fully developed. Accepted short papers will be presented in a short lightning talk.


Relevant review criteria:


novelty

soundness of approach

relevance to the conference (+ clarity of relation with related work)

quality of presentation

quality of evaluation [for long papers]

ability to replicate [for long papers]


2. Practice Experience


MSR encourages the submission of papers that report on both positive and negative experiences of applying software analytics strategies in an industry/open source organization context. Adapting existing algorithms or proposing new algorithms or approaches for practical use are considered a plus.


Relevant review criteria:


quality of empirical evaluation

explicit discussion on the usefulness/impact of the approach in practice

explicit discussion of any adaptations required by the application of existing/new approach in practice

quality of presentation

relevance to the conference (+ clarity of relation with related work)


3. Reusable Tool


MSR actively promotes and recognizes the creation and use of tools that are designed and built not only for a specific research project, but for the MSR community as a whole. Those tools enable other researchers to jumpstart their own research efforts, and also enable reproducibility of earlier work.


Reusable Tool papers can be descriptions of tools built by the authors that can be used by other researchers, and/or descriptions of the use of tools built by others to obtain some specific research results in the area of mining software repositories.


Relevant review criteria:


evaluation of usefulness/reusability of the tool [for long papers]

novelty

quality of presentation (details on tool’s internals, usage, etc.)

relevance to the conference (+ clarity of relation with related work)

availability of the tool, clear installation instructions and example data set that allow the reviewers to run the tool


Submission Process


All types of technical papers will be peer-reviewed according to the specified review criteria, hence it is required to choose the right type of paper according to the paper’s major contributions. Submissions should follow the ACM Conference Proceedings Formatting Guidelines (https://www.acm.org/publications/proceedings-template ). LaTeX users must use the provided acmart.cls and ACM-Reference-Format.bst without modification, enable the conference format in the preamble of the document (i.e., \documentclass[sigconf,review]{acmart}), and use the ACM reference format for the bibliography (i.e., \bibliographystyle{ACM-Reference-Format}). The review option adds line numbers, thereby allowing referees to refer to specific lines in their comments.


Papers submitted for consideration should not have been published elsewhere and should not be under review or submitted for review elsewhere for the duration of consideration. ACM plagiarism policies and procedures shall be followed for cases of double submission. The submission must also comply with the IEEE Policy on Authorship. Please read the ACM Policy and Procedures on Plagiarism (https://www.acm.org/publications/policies/plagiarism) and the IEEE Plagiarism FAQ (https://www.ieee.org/publications/rights/plagiarism/plagiarism-faq.html) before submitting.


Upon notification of acceptance, all authors of accepted papers will be asked to complete a copyright form and will receive further instructions for preparing their camera ready versions. At least one author of each paper is expected to register and present the results at the MSR 2020 conference. All accepted contributions will be published in the conference electronic proceedings.


A selection of the best papers will be invited to an EMSE Special Issue. All accepted technical papers in 2020 have a chance to nominate their paper for the "MSR FOSS Impact Paper Award“.


IMPORTANT: MSR 2020 follows the double-blind submission model. Submissions should not reveal the identity of the authors in any way. This means that authors should:


leave out author names and affiliations from the body and metadata of the submitted pdf

ensure that any citations to related work by themselves are written in the third person, for example “the prior work of XYZ” as opposed to “our prior work [2]”

not refer to their personal, lab or university website; similarly, care should be taken with personal accounts on github, bitbucket, Google Drive, etc.

not upload unblinded versions of their paper on archival websites during bidding/reviewing, however uploading unblinded versions prior to submission is allowed and sometimes unavoidable (e.g., thesis)


Please note that double-blind submission should not be an excuse for hiding replication packages or data sets from reviewers, since that effectively hinders the peer-review process. Since access to data and scripts is essential during peer review, we strongly recommend to archive data sets on online archival sites such as dropbox.com, zenodo.org or figshare.com (Instructions available in Open Science Policy below). The latter two even allow to receive a DOI and hence become citable.


Submission Link


Technical papers must be submitted through EasyChair: https://easychair.org/conferences/?conf=msr20


Open Science Policy


Openness in science is key to fostering progress via transparency, reproducibility and replicability. Our steering principle is that all research output should be accessible to the public and that empirical studies should be reproducible. In particular, we actively support the adoption of open data and open source principles. The following guidelines are recommendations and not mandatory. Your choice to use open science or not will not affect the review process for your paper. However, to increase reproducibility and replicability, we encourage all contributing authors to disclose:


the source code of relevant software used or proposed in the paper, including that used to retrieve and analyze data

the data used in the paper (e.g., evaluation data, anonymized survey data etc)

instructions for other researchers describing how to reproduce or replicate the results


Already upon submission, authors can privately share their anonymized data and software on preserved archives such as Zenodo or Figshare (tutorial available here – please make sure to any links shared during peer review are anonymized). Zenodo accepts up to 50GB per dataset (more upon request). There is no need to use Dropbox or Google Drive. Once accepted, an option can be toggled to publish the data and scripts with an official DOI. Zenodo and Figshare accounts can easily be linked with GitHub repositories to automatically archive software releases. In the unlikely case that authors need to upload terabytes of data, Archive.org may be used.


After acceptance, we encourage authors to self-archive pre-prints of their papers in open, preserved repositories such as arXiv.org. This is legal and allowed by all major publishers including ACM and IEEE and it lets anybody in the world reach your paper. Note that you are usually not allowed to self-archive the PDF of the published article (that is, the publisher proof or the Digital Library version). Instead, use the manuscript with reviewer comments addressed, but before applying the camera-ready instructions and templates. Feel free to contact the MSR 2020 PC or proceedings chairs for more details.


Please note that the success of the open science initiative depends on the willingness (and possibilities) of authors to disclose their data and that all submissions will undergo the same review process independent of whether or not they disclose their analysis code or data. We encourage authors who cannot disclose industrial or otherwise non-public data, for instance due to non-disclosure agreements, to provide an explicit (short) statement in the paper.

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