MutaBot: A Mutation Testing Approach for Chatbots Article Swipe
Michael Ferdinando Urrico
,
Diego Clerissi
,
Leonardo Mariani
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2401.10372
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2401.10372
Mutation testing is a technique aimed at assessing the effectiveness of test suites by seeding artificial faults into programs. Although available for many platforms and languages, no mutation testing tool is currently available for conversational chatbots, which represent an increasingly popular solution to design systems that can interact with users through a natural language interface. Note that since conversations must be explicitly engineered by the developers of conversational chatbots, these systems are exposed to specific types of faults not supported by existing mutation testing tools. In this paper, we present MutaBot, a mutation testing tool for conversational chatbots. MutaBot addresses mutations at multiple levels, including conversational flows, intents, and contexts. We designed the tool to potentially target multiple platforms, while we implemented initial support for Google Dialogflow chatbots. We assessed the tool with three Dialogflow chatbots and test cases generated with Botium, revealing weaknesses in the test suites.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2401.10372
- https://arxiv.org/pdf/2401.10372
- OA Status
- green
- References
- 18
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4391125503
All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4391125503Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2401.10372Digital Object Identifier
- Title
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MutaBot: A Mutation Testing Approach for ChatbotsWork title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-01-18Full publication date if available
- Authors
-
Michael Ferdinando Urrico, Diego Clerissi, Leonardo MarianiList of authors in order
- Landing page
-
https://arxiv.org/abs/2401.10372Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2401.10372Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
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https://arxiv.org/pdf/2401.10372Direct OA link when available
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Computer science, Mutation, Test (biology), Chatbot, Mutation testing, Interface (matter), Human–computer interaction, Software engineering, Natural language processing, Artificial intelligence, Operating system, Biology, Bubble, Gene, Biochemistry, Maximum bubble pressure method, Paleontology, ChemistryTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
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18Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.assessed | 129 |
| abstract_inverted_index.chatbots | 135 |
| abstract_inverted_index.designed | 111 |
| abstract_inverted_index.existing | 81 |
| abstract_inverted_index.intents, | 107 |
| abstract_inverted_index.interact | 47 |
| abstract_inverted_index.language | 53 |
| abstract_inverted_index.multiple | 102, 117 |
| abstract_inverted_index.mutation | 27, 82, 92 |
| abstract_inverted_index.solution | 41 |
| abstract_inverted_index.specific | 74 |
| abstract_inverted_index.addresses | 99 |
| abstract_inverted_index.assessing | 7 |
| abstract_inverted_index.available | 20, 32 |
| abstract_inverted_index.chatbots, | 35, 68 |
| abstract_inverted_index.chatbots. | 97, 127 |
| abstract_inverted_index.contexts. | 109 |
| abstract_inverted_index.currently | 31 |
| abstract_inverted_index.generated | 139 |
| abstract_inverted_index.including | 104 |
| abstract_inverted_index.mutations | 100 |
| abstract_inverted_index.platforms | 23 |
| abstract_inverted_index.programs. | 18 |
| abstract_inverted_index.represent | 37 |
| abstract_inverted_index.revealing | 142 |
| abstract_inverted_index.supported | 79 |
| abstract_inverted_index.technique | 4 |
| abstract_inverted_index.Dialogflow | 126, 134 |
| abstract_inverted_index.artificial | 15 |
| abstract_inverted_index.developers | 65 |
| abstract_inverted_index.engineered | 62 |
| abstract_inverted_index.explicitly | 61 |
| abstract_inverted_index.interface. | 54 |
| abstract_inverted_index.languages, | 25 |
| abstract_inverted_index.platforms, | 118 |
| abstract_inverted_index.weaknesses | 143 |
| abstract_inverted_index.implemented | 121 |
| abstract_inverted_index.potentially | 115 |
| abstract_inverted_index.increasingly | 39 |
| abstract_inverted_index.conversations | 58 |
| abstract_inverted_index.effectiveness | 9 |
| abstract_inverted_index.conversational | 34, 67, 96, 105 |
| cited_by_percentile_year | |
| corresponding_author_ids | https://openalex.org/A5036120394 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 3 |
| corresponding_institution_ids | https://openalex.org/I66752286 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/4 |
| sustainable_development_goals[0].score | 0.7300000190734863 |
| sustainable_development_goals[0].display_name | Quality Education |
| citation_normalized_percentile.value | 0.04438642 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |