Replication Package for the Paper: "Will Data Influence the Experiment Results?: A Replication Study of Automatic Identification of Decisions"

This is the replication package for the paper: "Will Data Influence the Experiment Results?: A Replication Study of Automatic Identification of Decisions". It contains the source code and dataset of our experiment for the replication by other researchers. In the meanwhile, we provide brief description of the files in the replication package below.

1. main_code folder

• automatic_approach.py  contains the main source code of the automatic approach for identifying decisions in our experiment, which is conducted on MacOs and Python 3.7.9. Note that you may get slightly different experiment results when conducting the experiments on different environment configurations.
• requirement.txt  records all the installation packages and their version numbers needed for the current program to run. You can use "pip install -r requirement.txt" to rebuild the project and install all dependencies. Note that you may get slightly different experiment results when using different packages or versions. 

2. dataset folder

• EASE2020 - 650 decisions.xlsx  contains 650 decision sentences from our previous work (EASE2020)
• EASE2020 - 650 non decisions.xlsx  contains 650 non-decision sentences from our previous work (EASE2020)
• Our 844 relabeled decisions.xlsx contains 844 relabeled decisions in this work.
• Our 750 assumptions.xlsx contains 750 assumptions from our previous work (APSEC2019)

3. RQ1 folder

• experiment_RQ1.py contains the main source code of the experiment for answering RQ1, which is conducted on the same environment configuration as the automatic_approach.py.

4. RQ2 folder

• experiment_RQ2.py contains the main source code of the experiment for answering RQ2, which is conducted on the same environment configuration as the automatic_approach.py.

5. RQ3 folder

• experiment_RQ3.py contains the main source code of the experiment for answering RQ3, which is conducted on the same environment configuration as the automatic_approach.py.