{'fraction_non_alphanumeric': 0.016842105263157894, 'fraction_numerical': 0.0, 'mean_word_length': 5.215686274509804, '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}}
Analyzing Exceptions in the Context of Test Data Generation Based on Symbolic Execution

Testing exception scenarios is a challenging task in the context of test data generation based on symbolic execution. In such a context, test data is generated based on constraints explicitly declared in the code. However, constraints required to activate specific exceptions may not be directly declared in the code. In such a case, implicit constraints have to be inferred from exception handling mechanisms. Given that exceptions can be raised in several situations, finding constraints to generate test data to exercise all possible faulty scenarios can significantly increase the number of paths and constraints, which can cause or aggravate path explosion issues. This paper reports on an investigation that we carried out to gauge the cost (i.e., number of path constraints) of four data generation approaches aimed at covering exception dependent paths.