{'fraction_non_alphanumeric': 0.025, 'fraction_numerical': 0.0014285714285714286, 'mean_word_length': 5.671428571428572, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Experimental Comparison of Two Goal-oriented Analysis Techniques

Background: Goal-oriented analysis techniques help reason and make decisions about goal models. These models may represent the stakeholders’ intentions with respect to the software system to be developed. In a previous work, we proposed VeGAn, a goal-oriented analysis technique that follows a value-driven approach in order to support decision-making. Aims: This paper compares the VeGAn technique with the GRL-Quant technique, with respect to the accuracy of goal model element prioritization, the participants’ prioritization time, and their perceptions of the quality of the analysis results (perceived satisfaction). Method: A controlled experiment was carried out with 64 Computer Science undergraduate students who analyzed a goal model using each of the techniques compared. Results: The results of the experiment show that there are no significant differences between prioritization time. However, the perceived satisfaction was superior for VeGAn, although the prioritization accuracy of GRL-Quant was better for one particular system. Conclusions: While further research is required in order to strengthen these results, the experiment provides preliminary results on the usefulness of both goal-oriented analysis techniques. Several insights have emerged from this study, and also opportunities to improve both techniques.