Software merging is a time-consuming and error-prone activity but essential to large-scale software development. Developers use software merging tools, but if such tools return results with too many conflicts and errors, this activity becomes even more difficult. To help developers, several algorithms have been proposed to improve the automation of merge tools. These algorithms aim at minimising conflict situations and therefore improving the productivity of the development team, however no general framework is proposed to evaluated and compare their result. This paper proposes a methodology to measure the effort required to use the result of a given merge tool. We employ the large number of publicly available open-source development histories to automatically compute this measure and evaluate the quality of the merging tools results. We use the simple idea that these histories contains both the concurrent modifications and their merge results as approved by the developers. Through a study of six open-source repositories totalling more than 2.5 millions lines of code, we show meaningful comparison results between merge algorithms and how to use the results to improve them.