{'fraction_non_alphanumeric': 0.019897669130187607, 'fraction_numerical': 0.0, 'mean_word_length': 5.518518518518518, '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}}
Organizing the Design Thinking Toolbox: Supporting the Requirements Elicitation Decision Making

Context: Requirements Elicitation is an essential part of the software development process. Design Thinking (DT) arises as an alternative approach for supporting the Requirements Elicitation step. Empirical studies have shown that the use of DT in the software development process can be beneficial. The literature offers a wide variety of DT techniques. However, there is a lack of studies that mention which information is needed to use the techniques and which results they generate. Objective: Motivated by this need, this work aims to assist the software engineers in selecting which DT techniques are more suitable to support the requirements elicitation step. Method: We performed a literature review to identify DT techniques that can be used for the requirements elicitation. Next, we analysed and modelled the techniques identified using SADT diagrams. We grouped the DT techniques into ten categories according to their main purpose. Based on the SADT diagrams, we elaborated a comparative table for these categories, showing for each technique: input, control, mechanism, and output terms. We carried out a feasibility study to verify whether the comparison tables among the DT techniques provide the necessary information for software engineers. Results: Our preliminary results showed that the comparative tables, describing the inputs, control, mechanism, and outputs, helped software engineers to select the DT technique according to their goals. Conclusion: The results provided evidence that the DT techniques comparison table is promising in the context of requirements elicitation decision making to choose the most appropriate DT techniques.