Draft of the first consistent version of the README.

README.md

-# Tree Edit Distance similarity join - experiments
+# Tree Edit Distance Experiments
 
-## Building
+Currently the experiments framework contains stand-alone tree edit distance
+and tree similarity join algorithms.
+
+Follow the instructions below to reproduce the environment and the experiments.
+
+## ICDE 2019 Reproducibility
+
+For reproducing the experiments of the ICDE 2019 submission, checkout the tag
+`icde2019` of this and Tree Similarity library repositories.
+
+Obtain datasets from our
+[Datasets repository](https://frosch.cosy.sbg.ac.at/mpawlik/ted-datasets)
+
+Execute the experiments with all config files in `configs/icde2019` directory.
+
+Plot the results using `src/plots/call_plot.sh` file.
+
+## Build the project
+
+After cloning the repository, clone the external libraries to `external`
+subdirectory.
 
-First clone the external libraries. Execute the following from the project's root directory.
 ```bash
 mkdir external
 cd external
-# Timing library.
+```
+Clone the Timing library for runtime measurements.
+
+```bash
 git clone git@frosch.cosy.sbg.ac.at:wmann/common-code.git
-# Tree Similarity library.
-git clone -b develop https://github.com/DatabaseGroup/tree-similarity.git
+```
+
+Clone the Tree Similarity library with the algorithms (the `develop` branch
+is currently the most recent).
+
+```bash
+git clone --branch develop https://github.com/DatabaseGroup/tree-similarity.git
 ```
 
 Then execute the following from the project's root directory.
@@ -20,16 +47,60 @@ cmake ..
 make
 ```
 
-## PostgreSQL
+## Prepare a PostgreSQL database for storing the results
+
+Install [PostgreSQL](https://www.postgresql.org/).
 
-Create a database using the SQL file ``./db/create_db.sql``.
+Create a database using the SQL file ``db/create_db.sql``.
+
+Create a service file ``~/.pg_service.conf`` on the machine where you execute
+the experiments. The service file holds the connection details to the database
+where the results will be stored. An example service file looks as follows.
+
+```
+[ted-experiments]
+host=mydb.sbg.ac.at
+port=5432
+user=ted
+password=letmethrough
+dbname=ted_experiments
+```
+
+Executing experiments requires dataset details to be present in the `dataset`
+table. Visit our
+[Datasets repository](https://frosch.cosy.sbg.ac.at/mpawlik/ted-datasets)
+to learn how we obtain datasets. Use the `--service service` option of the
+`statistics/statistics.py` script to register a dataset in the `dataset` table.
 
-Further, create ``~/.pg_service.conf`` on the machine where you execute the experiments. 
-Insert a service for the database used to store experimental results.
 
 ## Executing
 
-Use Python3 to run the experiments script by executing the following command from the root directory of the repository. 
+We use [Python3](https://www.python.org/) to execute the experiments.
+
+### TED Join
+
+The script `src/join_algs/join_algs_experiments.py` executes tree similarity
+join experiments.
+
+It uses a config JSON file to specify the experiment parameters. Example config
+files can be found in `configs/icde2019` directory.
+
+Example experiment execution can be performed as follows.
+
 ```bash
 python3 src/join_algs/join_algs_experiments.py --config configs/icde2019/bolzano.json --dataset_path /path_to/ted-datasets/ --service service
 ```
+
+### TED Algorithms
+
+The script `src/ted_algs/ted_algs_experiments.py` executes tree similarity
+join experiments.
+
+It uses a config JSON file to specify the experiment parameters. Example config
+files can be found in `configs/icde2019/upperbound` directory.
+
+Example experiment execution can be performed as follows.
+
+```bash
+python3 src/join_algs/ted_algs_experiments.py --config configs/icde2019/upperbound/sentiment.json --dataset_path /path_to/ted-datasets/ --service service
+```
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