Add files via upload

Author: oliviaguest

10.5281_zenodo.6255131/article.pdf

@@ -0,0 +1,120 @@
+# To be filled by the author(s) at the time of submission
+# -------------------------------------------------------
+
+# Title of the article:
+#  - For a successful replication, it shoudl be prefixed with "[Re]"
+#  - For a failed replication, it should be prefixed with "[¬Re]"
+#  - For other article types, no instruction (but please, not too long)
+title: "[Re] Effective Program Debloating via Reinforcement Learning"
+
+# List of authors with name, orcid number, email and affiliation
+# Affiliation "*" means contact author
+authors:
+  - name: Denis Maurel
+    orcid: 0000-0001-5658-5923
+    email: [email protected]
+    affiliations: 1,*
+
+  - name: Jérôme Fillioux
+    orcid: 0000-0001-7304-1899
+    email: [email protected]
+    affiliations: 1
+
+  - name: Dan Gugenheim
+    orcid: 0000-0003-4800-7909
+    email: [email protected]
+    affiliations: 1
+
+# List of affiliations with code (corresponding to author affiliations), name
+# and address. You can also use these affiliations to add text such as "Equal
+# contributions" as name (with no address).
+affiliations:
+  - code:    1
+    name:    onepoint sud-ouest R&D
+    address: Bordeaux, France
+
+# List of keywords (adding the programming language might be a good idea)
+keywords: program debloating, reinforcement learning, unit test, python, machine learning, decision tree, delta debugging
+
+# Code URL and DOI (url is mandatory for replication, doi after acceptance)
+# You can get a DOI for your code from Zenodo,
+#   see https://guides.github.com/activities/citable-code/
+code:
+  - url: https://gitlab.com/onepoint/recherche-et-developpement/optimus/chisel-replication
+  - doi: 10.5281/zenodo.4530318
+
+# Date URL and DOI (optional if no data)
+data:
+  - url:
+  - doi:
+
+# Information about the original article that has been replicated
+replication:
+ - cite: Heo, K., Lee, W., Pashakhanloo, P., & Naik, M. (2018, October).Effective program debloating via reinforcement learning. In Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security (pp. 380-394).
+ - bib:  heoEffectiveProgramDebloating2018
+ - url:  https://www.cis.upenn.edu/~mhnaik/papers/chisel.pdf
+ - doi:  10.1145/3243734.3243838
+
+
+# Don't forget to surround abstract with double quotes
+abstract: "This paper presents a replication of the CHISEL debloating system with some clarifications on caveats of the original method.
+           It also presents a new property testing method using unit tests.
+           The original results are extended with numerical proves of the improvements linked to the Reinforcement
+           Learning part of the CHISEL system compared to the original HDD system.
+           Several Python librairies are debloated and the improvements in terms of number of iterations and time consumption are presented.
+           The results show that the RL part of CHISEL significantly improves the original HDD algorithm."
+
+# Bibliography file (yours)
+bibliography: bibliography.bib
+
+# Type of the article
+# Type can be:
+#  * Editorial
+#  * Letter
+#  * Replication
+type: Replication
+
+# Scientific domain of the article (e.g. Computational Neuroscience)
+#  (one domain only & try to be not overly specific)
+domain: Program Debloating
+
+# Coding language (main one only if several)
+language: Python
+
+
+# To be filled by the author(s) after acceptance
+# -----------------------------------------------------------------------------
+
+# For example, the URL of the GitHub issue where review actually occured
+review:
+  - url: https://github.com/ReScience/submissions/issues/48
+
+contributors:
+  - name: Olivia Guest
+    orcid: 0000-0002-1891-0972
+    role: editor
+  - name: Wouter Kouw
+    orcid: 0000-0002-0547-4817
+    role: reviewer
+  - name: Esther Mulwa
+    orcid: 0000-0002-1327-1198
+    role: reviewer
+
+# This information will be provided by the editor
+dates:
+  - received: February 10, 2021
+  - accepted: January 18, 2022
+  - published: March 28, 2022
+
+# This information will be provided by the editor
+article:
+  - number: 12 # Article number will be automatically assigned during publication
+  - doi: 10.5281/zenodo.6255131 # DOI from Zenodo
+  - url: https://zenodo.org/record/6255131/files/article.pdf # Final PDF URL (Zenodo or rescience website?)
+
+# This information will be provided by the editor
+journal:
+  - name:   "ReScience C"
+  - issn:   2430-3658
+  - volume: 7
+  - issue:  1