Script languages are powerful tools for scientists. Scientists use them to process data, invoke programs, and link program outputs/inputs. During the life cycle of scientific experiments, scientists compose scripts, execute them, and perform analysis on the results. Depending on the results, they modify their script to get more data to confirm the original hypothesis or to test a new hypothesis, evolving the experiment. While some tools capture provenance from the execution of scripts, most approaches focus on a single execution, leaving out the possibility to analyze the provenance evolution of the experiment as a whole. This work enables tracking and analyzing the provenance evolution gathered from scripts. Tracking the provenance evolution also helps to reconstruct the environment of previous executions for reproduction. Provenance evolution analysis allows comparison of executions to understand what has changed and supports the decision of which execution provides better results.