{"id":{"repo_id":"iastate","oai_identifier":"oai:dr.lib.iastate.edu:20.500.12876/aw4NZV7r"},"canonical_url":"https://search.dev.ndltd.org/etd/iastate/oai:dr.lib.iastate.edu:20.500.12876/aw4NZV7r","repository":{"repo_id":"iastate","name":"Iowa State University","base_url":"https://dr.lib.iastate.edu/server/oai/request"},"display":{"title":"Regression testing of an evolving quantum platform","abstract":"Quantum computing is a field that has drawn a lot of attention over the years as it has shown great potential to solve new problems and has seen rapid development. To meet the demands of this rapid development, software engineering researchers have been studying methods to address the unique challenges presented by the probabilistic nature of quantum computing in its software platforms. One important aspect of this is understanding how to test and validate quantum software platforms when the expected outputs when running a program are not always known. Recent research using metamorphic testing was able to detect 13 faults in the Qiskit quantum computing platform; however, this is a rapidly evolving platform. Since their work, Qiskit has already advanced ahead several versions, which brings up more questions regarding research for quantum software platforms: do these tools researchers create hold up across versions of these frequently-updated platforms, and how much work does it take to maintain and extend these tools? In this thesis, we study the ease of regression testing in the context of this quantum computing platform. We update to the latest version of Qiskit, extend two existing metamorphic transformations on a metamorphic testing platform for Qiskit, add six new metamorphic transformations, and perform a set of metamorphic testing runs to analyze how our changes perform. In doing so, we were able to discover five additional new faults on the Qiskit platform; however, we also uncovered several challenges, which we synthesize for the reader. We also offer discussion on where the future work of metamorphic testing on quantum software platforms may lead based on our challenges and successes during this process.","abstract_html":"Quantum computing is a field that has drawn a lot of attention over the years as it has shown great potential to solve new problems and has seen rapid development. To meet the demands of this rapid development, software engineering researchers have been studying methods to address the unique challenges presented by the probabilistic nature of quantum computing in its software platforms. One important aspect of this is understanding how to test and validate quantum software platforms when the expected outputs when running a program are not always known. Recent research using metamorphic testing was able to detect 13 faults in the Qiskit quantum computing platform; however, this is a rapidly evolving platform. Since their work, Qiskit has already advanced ahead several versions, which brings up more questions regarding research for quantum software platforms: do these tools researchers create hold up across versions of these frequently-updated platforms, and how much work does it take to maintain and extend these tools? In this thesis, we study the ease of regression testing in the context of this quantum computing platform. We update to the latest version of Qiskit, extend two existing metamorphic transformations on a metamorphic testing platform for Qiskit, add six new metamorphic transformations, and perform a set of metamorphic testing runs to analyze how our changes perform. In doing so, we were able to discover five additional new faults on the Qiskit platform; however, we also uncovered several challenges, which we synthesize for the reader. We also offer discussion on where the future work of metamorphic testing on quantum software platforms may lead based on our challenges and successes during this process.","abstract_has_math":false,"creators":["Kitt, Linsey"],"institution":"Iowa State University","degree_name":"Master of Science","degree_level":"thesis","degree_discipline":"Computer science","degree_department":"Department of Computer Science","school":null,"contributors":[],"advisors":["Cohen, Myra B","Lutz, Jack H","Iadecola, Thomas"],"committee_chairs":[],"committee_members":[],"year":2024,"date_issued":"2024-05","date_published":"2024-05","updated_at":"2026-07-24T02:39:07Z","subjects":[],"languages":["en"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier.doi","label":"DOI","values":["https://doi.org/10.31274/td-20240617-7"],"render_values":[{"text":"https://doi.org/10.31274/td-20240617-7","href":"https://doi.org/10.31274/td-20240617-7","code":true}]}]},"links":{"outbound_url":"https://dr.lib.iastate.edu/handle/20.500.12876/aw4NZV7r","outbound_label":"Repository record","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Cohen, Myra B","Lutz, Jack H","Iadecola, Thomas"]},{"key":"dc:contributor.department","label":"Department","values":["Department of Computer Science"]},{"key":"dc:creator","label":"Author","values":["Kitt, Linsey"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2024-06-05T22:07:41Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2024-06-05T22:07:41Z"]},{"key":"dc:date.issued","label":"Date","values":["2024-05"]},{"key":"dc:type","label":"Dc Type","values":["thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Computer science"]},{"key":"thesis:degree_level","label":"Degree Level","values":["thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["Iowa State University"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.doi","label":"DOI","values":["https://doi.org/10.31274/td-20240617-7"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://dr.lib.iastate.edu/handle/20.500.12876/aw4NZV7r"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Quantum computing is a field that has drawn a lot of attention over the years as it has shown great potential to solve new problems and has seen rapid development. To meet the demands of this rapid development, software engineering researchers have been studying methods to address the unique challenges presented by the probabilistic nature of quantum computing in its software platforms. One important aspect of this is understanding how to test and validate quantum software platforms when the expected outputs when running a program are not always known. Recent research using metamorphic testing was able to detect 13 faults in the Qiskit quantum computing platform; however, this is a rapidly evolving platform. Since their work, Qiskit has already advanced ahead several versions, which brings up more questions regarding research for quantum software platforms: do these tools researchers create hold up across versions of these frequently-updated platforms, and how much work does it take to maintain and extend these tools? In this thesis, we study the ease of regression testing in the context of this quantum computing platform. We update to the latest version of Qiskit, extend two existing metamorphic transformations on a metamorphic testing platform for Qiskit, add six new metamorphic transformations, and perform a set of metamorphic testing runs to analyze how our changes perform. In doing so, we were able to discover five additional new faults on the Qiskit platform; however, we also uncovered several challenges, which we synthesize for the reader. We also offer discussion on where the future work of metamorphic testing on quantum software platforms may lead based on our challenges and successes during this process."]},{"key":"dc:format.mimetype","label":"Dc Format Mimetype","values":["PDF"]},{"key":"dc:title","label":"Title","values":["Regression testing of an evolving quantum platform"]}]}],"canonical_facts":{"dc:contributor.advisor":["Cohen, Myra B","Lutz, Jack H","Iadecola, Thomas"],"dc:contributor.department":["Department of Computer Science"],"dc:creator":["Kitt, Linsey"],"dc:date.accessioned":["2024-06-05T22:07:41Z"],"dc:date.available":["2024-06-05T22:07:41Z"],"dc:date.issued":["2024-05"],"dc:description.abstract":["Quantum computing is a field that has drawn a lot of attention over the years as it has shown great potential to solve new problems and has seen rapid development. To meet the demands of this rapid development, software engineering researchers have been studying methods to address the unique challenges presented by the probabilistic nature of quantum computing in its software platforms. One important aspect of this is understanding how to test and validate quantum software platforms when the expected outputs when running a program are not always known. Recent research using metamorphic testing was able to detect 13 faults in the Qiskit quantum computing platform; however, this is a rapidly evolving platform. Since their work, Qiskit has already advanced ahead several versions, which brings up more questions regarding research for quantum software platforms: do these tools researchers create hold up across versions of these frequently-updated platforms, and how much work does it take to maintain and extend these tools? In this thesis, we study the ease of regression testing in the context of this quantum computing platform. We update to the latest version of Qiskit, extend two existing metamorphic transformations on a metamorphic testing platform for Qiskit, add six new metamorphic transformations, and perform a set of metamorphic testing runs to analyze how our changes perform. In doing so, we were able to discover five additional new faults on the Qiskit platform; however, we also uncovered several challenges, which we synthesize for the reader. We also offer discussion on where the future work of metamorphic testing on quantum software platforms may lead based on our challenges and successes during this process."],"dc:format.mimetype":["PDF"],"dc:identifier.doi":["https://doi.org/10.31274/td-20240617-7"],"dc:identifier.uri":["https://dr.lib.iastate.edu/handle/20.500.12876/aw4NZV7r"],"dc:language.iso":["en"],"dc:title":["Regression testing of an evolving quantum platform"],"dc:type":["thesis"],"thesis:degree_discipline":["Computer science"],"thesis:degree_level":["thesis"],"thesis:degree_name":["Master of Science"],"thesis:institution_name":["Iowa State University"]},"updated_at":"2026-07-24T02:39:07Z"}