Effective REST APIs Testing with Error Message Analysis
REST APIs are essential for building modern enterprise systems, but effectively testing them remains challenging, particularly due to difficulties in inferring constraints from specifications. Current testing approaches typically use feedback from HTTP status codes to guide input generation. However...
Saved in:
| Published in: | Proceedings of the ACM on software engineering Vol. 2; no. ISSTA; pp. 1978 - 2000 |
|---|---|
| Main Authors: | , , , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
New York, NY, USA
ACM
22.06.2025
|
| Subjects: | |
| ISSN: | 2994-970X, 2994-970X |
| Online Access: | Get full text |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Abstract | REST APIs are essential for building modern enterprise systems, but effectively testing them remains challenging, particularly due to difficulties in inferring constraints from specifications. Current testing approaches typically use feedback from HTTP status codes to guide input generation. However, they overlook valuable information available in the accompanying error messages, reducing their effectiveness in exploring the APIs’ input spaces. In this paper, we propose EmRest, a black-box testing approach that leverages error message analysis to enhance both valid and exceptional test input generation for REST APIs. For each operation under test, EmRest first identifies all possible value assignment strategies for each of its input parameters. It then repeatedly applies combinatorial testing to sample test inputs based on these strategies, and statistically analyzes the error messages (of 400-range status code) received to infer and exclude invalid combinations of value assignment strategies (i.e., constraints of the input space). Additionally, EmRest seeks to mutate valid value assignment strategies that are finally identified to generate test inputs for exceptional testing. The error messages (of 500-range status code) received are categorized to identify bug-prone operations, for which more testing resources are allocated. Our experimental results on 16 real-world REST APIs demonstrates the effectiveness of EmRest. It achieves higher operation coverage than state-of-the-art approaches in 50% of APIs, and detects 226 unique bugs undetected by other approaches. |
|---|---|
| AbstractList | REST APIs are essential for building modern enterprise systems, but effectively testing them remains challenging, particularly due to difficulties in inferring constraints from specifications. Current testing approaches typically use feedback from HTTP status codes to guide input generation. However, they overlook valuable information available in the accompanying error messages, reducing their effectiveness in exploring the APIs’ input spaces. In this paper, we propose EmRest, a black-box testing approach that leverages error message analysis to enhance both valid and exceptional test input generation for REST APIs. For each operation under test, EmRest first identifies all possible value assignment strategies for each of its input parameters. It then repeatedly applies combinatorial testing to sample test inputs based on these strategies, and statistically analyzes the error messages (of 400-range status code) received to infer and exclude invalid combinations of value assignment strategies (i.e., constraints of the input space). Additionally, EmRest seeks to mutate valid value assignment strategies that are finally identified to generate test inputs for exceptional testing. The error messages (of 500-range status code) received are categorized to identify bug-prone operations, for which more testing resources are allocated. Our experimental results on 16 real-world REST APIs demonstrates the effectiveness of EmRest. It achieves higher operation coverage than state-of-the-art approaches in 50% of APIs, and detects 226 unique bugs undetected by other approaches. |
| ArticleNumber | ISSTA087 |
| Author | Xu, Lixin Wang, Shaohua Nie, Changhai Niu, Xintao Wu, Huayao Xu, Tongtong Pan, Zhenyu |
| Author_xml | – sequence: 1 givenname: Lixin orcidid: 0009-0000-6085-345X surname: Xu fullname: Xu, Lixin email: lxxu@smail.nju.edu.cn organization: Nanjing University, Nanjing, China – sequence: 2 givenname: Huayao orcidid: 0000-0003-1383-5421 surname: Wu fullname: Wu, Huayao email: hywu@nju.edu.cn organization: Nanjing University, Nanjing, China – sequence: 3 givenname: Zhenyu orcidid: 0009-0001-4385-0908 surname: Pan fullname: Pan, Zhenyu email: zypan@smail.nju.edu.cn organization: Nanjing University, Nanjing, China – sequence: 4 givenname: Tongtong orcidid: 0000-0002-4323-497X surname: Xu fullname: Xu, Tongtong email: xutongtong9@huawei.com organization: Huawei, Hangzhou, China – sequence: 5 givenname: Shaohua orcidid: 0000-0001-5777-7759 surname: Wang fullname: Wang, Shaohua email: davidshwang@ieee.org organization: Central University of Finance and Economics, Beijing, China – sequence: 6 givenname: Xintao orcidid: 0000-0001-5786-0894 surname: Niu fullname: Niu, Xintao email: niuxintao@nju.edu.cn organization: Nanjing University, Suzhou, China – sequence: 7 givenname: Changhai orcidid: 0000-0002-9575-1012 surname: Nie fullname: Nie, Changhai email: changhainie@nju.edu.cn organization: Nanjing University, Nanjing, China |
| BookMark | eNpNj01LAzEYhINUsNbi3VNunlbfN5tskuNS1lqoKLoHb0s2H3Wl3ZWkKP33VlrF0wwzDwNzTkb90HtCLhFuELm4zSVTuuAnZMy05pmW8Dr658_INKV3ANgniBLGRFYheLvtPj19rl5qWj4tEq192nb9in512zdaxThE-uBTMitPy96sd6lLF-Q0mHXy06NOSH1X1bP7bPk4X8zKZWYE8szoNgiuhZOAOmfWoYOCSRvy4HOnHHBUojBomFEBhCuCsqZtHUNoC4Uhn5Drw6yNQ0rRh-YjdhsTdw1C8_O4OT7ek1cH0tjNH_RbfgNaklCT |
| Cites_doi | 10.1109/ASE56229.2023.00062 10.1145/3460319.3469082 10.1109/TSC.2021.3050610 10.1145/1883612.1883618 10.1145/3639476.3639769 10.1145/3533767.3534401 10.1109/DeepTest52559.2021.00008 10.1109/ASE51524.2021.9678586 10.1109/ICSE-Companion52605.2021.00040 10.1109/CCNS53852.2021.00023 10.1145/3597503.3639106 10.1109/ICST46399.2020.00023 10.1109/ICST60714.2024.00017 10.1145/3510003.3510133 10.1109/ICSE48619.2023.00213 10.53414/UIJES.2024.4.4.17 10.1109/ASE56229.2023.00218 10.1145/3180155.3182528 10.1007/s10009-024-00745-2 10.1145/3340433.3342822 10.1007/978-3-030-33702-5_31 10.1145/3368089.3409719 10.1145/3597926.3598131 10.1145/3293455 10.1145/3597205 10.1145/3510454.3528637 10.1109/ICST46399.2020.00062 10.1007/s10664-017-9570-9 10.1145/3468264.3473491 10.1109/ICST46399.2020.00024 10.1145/3617175 10.1109/TSE.2018.2865772 10.1109/edoc.2018.00031 10.1109/ISSRE59848.2023.00023 10.1145/3691620.3695532 10.1109/ICSE-SEIP52600.2021.00016 10.17487/RFC9457 10.1109/ICSE.2019.00083 10.1109/TSE.2004.24 10.17487/RFC7807 10.1007/978-3-031-48421-6_11 10.1145/3510003.3510151 10.1002/stvr.1808 |
| ContentType | Journal Article |
| Copyright | Copyright is held by the owner/author(s). Publication rights licensed to ACM. |
| Copyright_xml | – notice: Copyright is held by the owner/author(s). Publication rights licensed to ACM. |
| DBID | AAYXX CITATION |
| DOI | 10.1145/3728964 |
| DatabaseName | CrossRef |
| DatabaseTitle | CrossRef |
| DatabaseTitleList | CrossRef |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Computer Science |
| EISSN | 2994-970X |
| EndPage | 2000 |
| ExternalDocumentID | 10_1145_3728964 3728964 |
| GrantInformation_xml | – fundername: Primary Research and Development Plan of Jiangsu Province grantid: BE2023025-2 – fundername: Natural Science Foundation of Jiangsu Province grantid: BK20221439 funderid: https://doi.org/10.13039/501100004608 – fundername: National Natural Science Foundation of China grantid: 62472209 funderid: https://doi.org/10.13039/501100001809 |
| GroupedDBID | AAKMM ACM AEJOY AKRVB ALMA_UNASSIGNED_HOLDINGS LHSKQ M~E AAYXX CITATION |
| ID | FETCH-LOGICAL-a514-a9bf5495d701932cd1d0627cf3fe3d8d041856a1a2a8f05d6f8cabbd210b681f3 |
| ISSN | 2994-970X |
| IngestDate | Sat Nov 29 07:43:49 EST 2025 Mon Jul 14 20:48:59 EDT 2025 |
| IsDoiOpenAccess | true |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | ISSTA |
| Keywords | Feedback-Driven Testing OpenAPI REST APIs |
| Language | English |
| License | Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from permissions@acm.org. |
| LinkModel | OpenURL |
| MergedId | FETCHMERGED-LOGICAL-a514-a9bf5495d701932cd1d0627cf3fe3d8d041856a1a2a8f05d6f8cabbd210b681f3 |
| ORCID | 0000-0002-4323-497X 0009-0001-4385-0908 0009-0000-6085-345X 0000-0001-5777-7759 0000-0002-9575-1012 0000-0003-1383-5421 0000-0001-5786-0894 |
| OpenAccessLink | https://dl.acm.org/doi/10.1145/3728964 |
| PageCount | 23 |
| ParticipantIDs | crossref_primary_10_1145_3728964 acm_primary_3728964 |
| PublicationCentury | 2000 |
| PublicationDate | 20250622 2025-06-22 |
| PublicationDateYYYYMMDD | 2025-06-22 |
| PublicationDate_xml | – month: 06 year: 2025 text: 20250622 day: 22 |
| PublicationDecade | 2020 |
| PublicationPlace | New York, NY, USA |
| PublicationPlace_xml | – name: New York, NY, USA |
| PublicationTitle | Proceedings of the ACM on software engineering |
| PublicationTitleAbbrev | ACM PACMSE |
| PublicationYear | 2025 |
| Publisher | ACM |
| Publisher_xml | – name: ACM |
| References | SpringDoc Contributors. 2024. SpringDoc OpenAPI. https://springdoc.org/ Accessed: 2025-02-11 Yi Liu, Yuekang Li, Gelei Deng, Yang Liu, Ruiyuan Wan, Runchao Wu, Dandan Ji, Shiheng Xu, and Minli Bao. 2022. Morest: model-based RESTful API testing with execution feedback. In Proceedings of the 44th International Conference on Software Engineering (ICSE ’22). Association for Computing Machinery, New York, NY, USA. 1406–1417. isbn:9781450392211 https://doi.org/10.1145/3510003.3510133 10.1145/3510003.3510133 Wu Biao, Tang Chaojing, and Zhang Bin. 2021. FFUZZ: A Fast Fuzzing Test Method for Stateful Network Protocol Implementation. In 2021 2nd International Conference on Computer Communication and Network Security (CCNS). 75–79. https://doi.org/10.1109/CCNS53852.2021.00023 10.1109/CCNS53852.2021.00023 Hamza Ed-douibi, Javier Luis Cánovas Izquierdo, and Jordi Cabot. 2018. Automatic Generation of Test Cases for REST APIs: A Specification-Based Approach. 2018 IEEE 22nd International Enterprise Distributed Object Computing Conference (EDOC), 181–190. https://doi.org/10.1109/edoc.2018.00031 10.1109/edoc.2018.00031 Jinkun Lin, Shaowei Cai, Bing He, Yingjie Fu, Chuan Luo, and Qingwei Lin. 2021. FastCA: An Effective and Efficient Tool for Combinatorial Covering Array Generation. In 2021 IEEE/ACM 43rd International Conference on Software Engineering: Companion Proceedings (ICSE-Companion). 77–80. https://doi.org/10.1109/ICSE-Companion52605.2021.00040 10.1109/ICSE-Companion52605.2021.00040 2024. The Official YAML Web Site. https://yaml.org/ Accessed: 2024-07-04 Xintao Niu, Changhai Nie, Hareton Leung, Yu Lei, Xiaoyin Wang, Jiaxi Xu, and Yan Wang. 2020. An Interleaving Approach to Combinatorial Testing and Failure-Inducing Interaction Identification. IEEE Transactions on Software Engineering, 46, 6 (2020), 584–615. https://doi.org/10.1109/TSE.2018.2865772 10.1109/TSE.2018.2865772 Myeongsoo Kim, Qi Xin, Saurabh Sinha, and Alessandro Orso. 2022. Automated test generation for REST APIs: no time to rest yet. In Proceedings of the 31st ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA 2022). Association for Computing Machinery, New York, NY, USA. 289–301. isbn:9781450393799 https://doi.org/10.1145/3533767.3534401 10.1145/3533767.3534401 Vaggelis Atlidakis, Patrice Godefroid, and Marina Polishchuk. 2019. RESTler: stateful REST API fuzzing. In Proceedings of the 41st International Conference on Software Engineering (ICSE ’19). IEEE Press, 748–758. https://doi.org/10.1109/ICSE.2019.00083 10.1109/ICSE.2019.00083 Amid Golmohammadi, Man Zhang, and Andrea Arcuri. 2023. Testing RESTful APIs: A Survey. ACM Trans. Softw. Eng. Methodol., 33, 1 (2023), Article 27, nov, 41 pages. issn:1049-331X https://doi.org/10.1145/3617175 10.1145/3617175 Swaroopa Dola, Rory McDaniel, Matthew B. Dwyer, and Mary Lou Soffa. 2024. CIT4DNN: Generating Diverse and Rare Inputs for Neural Networks Using Latent Space Combinatorial Testing. In Proceedings of the IEEE/ACM 46th International Conference on Software Engineering (ICSE ’24). Association for Computing Machinery, New York, NY, USA. Article 118, 13 pages. isbn:9798400702174 https://doi.org/10.1145/3597503.3639106 10.1145/3597503.3639106 Alberto Martin-Lopez, Sergio Segura, Carlos Müller, and Antonio Ruiz-Cortés. 2022. Specification and Automated Analysis of Inter-Parameter Dependencies in Web APIs. IEEE Transactions on Services Computing, 15, 4 (2022), 2342–2355. https://doi.org/10.1109/TSC.2021.3050610 10.1109/TSC.2021.3050610 2024. MITMProxy. https://mitmproxy.org/ Accessed: 2024-07-04 Postman API Evangelist. 2024. Postman to OpenAPI Collection. https://www.postman.com/api-evangelist/artificial-intelligence/collection/txy0rdd/postman-to-openapi Accessed: 2025-02-11 2024. YouTube Data API Specification. https://api.apis.guru/v2/specs/googleapis.com/youtube/v3/openapi.yaml Accessed: 2024-10-29 Zac Hatfield-Dodds and Dmitry Dygalo. 2022. Deriving semantics-aware fuzzers from web API schemas. In Proceedings of the ACM/IEEE 44th International Conference on Software Engineering: Companion Proceedings (ICSE ’22). Association for Computing Machinery, New York, NY, USA. 345–346. isbn:9781450392235 https://doi.org/10.1145/3510454.3528637 10.1145/3510454.3528637 Patrice Godefroid, Bo-Yuan Huang, and Marina Polishchuk. 2020. Intelligent REST API data fuzzing. In Proceedings of the 28th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE 2020). Association for Computing Machinery, New York, NY, USA. 725–736. isbn:9781450370431 https://doi.org/10.1145/3368089.3409719 10.1145/3368089.3409719 2025. Replication package. https://zenodo.org/records/14940931 Accessed: 2025-02-28 Myeongsoo Kim, Davide Corradini, Saurabh Sinha, Alessandro Orso, Michele Pasqua, Rachel Tzoref-Brill, and Mariano Ceccato. 2023. Enhancing REST API Testing with NLP Techniques. In Proceedings of the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA 2023). Association for Computing Machinery, New York, NY, USA. 1232–1243. isbn:9798400702211 https://doi.org/10.1145/3597926.3598131 10.1145/3597926.3598131 D.R. Kuhn, D.R. Wallace, and A.M. Gallo. 2004. Software fault interactions and implications for software testing. IEEE Transactions on Software Engineering, 30, 6 (2004), 418–421. https://doi.org/10.1109/TSE.2004.24 10.1109/TSE.2004.24 RobBagby. 2023. Web API Implementation - Best Practices for Cloud Applications. https://learn.microsoft.com/en-us/azure/architecture/best-practices/api-implementation. 2024. Built-in String Formats of OpenAPI. https://swagger.io/docs/specification/data-models/data-types/##string Accessed: 2024-07-02 Myeongsoo Kim, Saurabh Sinha, and Alessandro Orso. 2023. Adaptive REST API Testing with Reinforcement Learning. IEEE Computer Society, 446–458. isbn:9798350329964 https://doi.org/10.1109/ASE56229.2023.00218 10.1109/ASE56229.2023.00218 Man Zhang and Andrea Arcuri. 2023. Open Problems in Fuzzing RESTful APIs: A Comparison of Tools. ACM Trans. Softw. Eng. Methodol., 32, 6 (2023), Article 144, sep, 45 pages. issn:1049-331X https://doi.org/10.1145/3597205 10.1145/3597205 Davide Corradini, Michele Pasqua, and Mariano Ceccato. 2023. Automated Black-Box Testing of Mass Assignment Vulnerabilities in RESTful APIs. In Proceedings of the 45th International Conference on Software Engineering (ICSE ’23). IEEE Press, 2553–2564. isbn:9781665457019 https://doi.org/10.1109/ICSE48619.2023.00213 10.1109/ICSE48619.2023.00213 Tri Le, Thien Tran, Duy Cao, Vy Le, Tien N. Nguyen, and Vu Nguyen. 2024. KAT: Dependency-Aware Automated API Testing with Large Language Models. In 2024 IEEE Conference on Software Testing, Verification and Validation (ICST). IEEE Computer Society, Los Alamitos, CA, USA. 82–92. issn:2159-4848 https://doi.org/10.1109/ICST60714.2024.00017 10.1109/ICST60714.2024.00017 Xinyi Wang, Paolo Arcaini, Tao Yue, and Shaukat Ali. 2024. QuCAT: A Combinatorial Testing Tool for Quantum Software. In Proceedings of the 38th IEEE/ACM International Conference on Automated Software Engineering (ASE ’23). IEEE Press, 2066–2069. isbn:9798350329964 https://doi.org/10.1109/ASE56229.2023.00062 10.1109/ASE56229.2023.00062 Emanuele Viglianisi, Michael Dallago, and Mariano Ceccato. 2020. RESTTESTGEN: Automated Black-Box Testing of RESTful APIs. In 2020 IEEE 13th International Conference on Software Testing, Validation and Verification (ICST). 142–152. issn:2159-4848 https://doi.org/10.1109/ICST46399.2020.00024 10.1109/ICST46399.2020.00024 Andrea Arcuri. 2019. RESTful API Automated Test Case Generation with EvoMaster. ACM Trans. Softw. Eng. Methodol., 28, 1 (2019), Article 3, jan, 37 pages. issn:1049-331X https://doi.org/10.1145/3293455 10.1145/3293455 2024. PICT. https://github.com/microsoft/pict Accessed: 2024-07-04 Davide Corradini, Amedeo Zampieri, Michele Pasqua, Emanuele Viglianisi, Michael Dallago, and Mariano Ceccato. 2022. Automated black-box testing of nominal and error scenarios in RESTful APIs. Software Testing, Verification and Reliability, 32, 5 (2022), e1808. Saman Barakat, Ana Belén Sánchez, and Sergio Segura. 2023. IDLGen: Automated Code Generation for Inter-parameter Dependencies in Web APIs. In Service-Oriented Computing: 21st International Conference, ICSOC 2023, Rome, Italy, November 28 – December 1, 2023, Proceedings, Part I. Springer-Verlag, Berlin, Heidelberg. 153–168. isbn:978-3-031-48420-9 https://doi.org/10.1007/978-3-031-48421-6_11 10.1007/978-3-031-48421-6_11 Adam Doupé, Ludovico Cavedon, Christopher Kruegel, and Giovanni Vigna. 2012. Enemy of the state: a state-aware black-box web vulnerability scanner. In Proceedings of the 21st USENIX Conference on Security Symposium (Security’12). USENIX Association, USA. 26. 2024. JaCoCo. https://www.eclemma.org/jacoco/ Accessed: 2024-07-02 Mark Nottingham and Erik Wilde. 2016. Problem Details for HTTP APIs. RFC 7807. https://doi.org/10.17487/RFC7807 10.17487/RFC7807 Van-Thuan Pham, Marcel Böhme, and Abhik Roychoudhury. 2020. AFLNET: A Greybox Fuzzer for Network Protocols. In 2020 IEEE 13th International Conference on Software Testing, Validation and Verification (ICST). 460–465. https://doi.org/10.1109/ICST46399.2020.00062 10.1109/ICST46399.2020.00062 Henk Grent, Aleksei Akimov, and Maurício Aniche. 2021. Automatically Identifying Parameter Constraints in Complex Web APIs: A Case Study at Adyen. In 2021 IEEE/ACM 43rd International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP). 71–80. https://doi.org/10.1109/ICSE-SEIP52600.2021.00016 10.1109/ICSE-SEIP52600.2021.00016 2024. FuzzyWuzzy. https://github.com/seatgeek/fuzzywuzzy Accessed: 2024-07-04 S. Karlsson, A. Causevic, and D. Sundmark. 2020. QuickREST: Property-based Test Generation of OpenAPI-Described RESTful APIs. In 2020 IEEE 13th International Conference on Software Testing, Validation and Verification (ICST). IEEE Computer Society, Los Alamitos, CA, USA. 131–141. issn:2159-4848 https://doi.org/10.1109/ICST4 Jiang Zu-Ming (e_1_2_1_30_1) 2023 e_1_2_1_60_1 e_1_2_1_41_1 e_1_2_1_45_1 e_1_2_1_62_1 e_1_2_1_43_1 e_1_2_1_28_1 e_1_2_1_49_1 e_1_2_1_26_1 e_1_2_1_47_1 e_1_2_1_31_1 e_1_2_1_54_1 e_1_2_1_8_1 e_1_2_1_56_1 e_1_2_1_6_1 e_1_2_1_12_1 e_1_2_1_35_1 e_1_2_1_50_1 e_1_2_1_4_1 Doupé Adam (e_1_2_1_22_1) 2012 e_1_2_1_10_1 e_1_2_1_33_1 e_1_2_1_52_1 e_1_2_1_2_1 e_1_2_1_16_1 e_1_2_1_39_1 e_1_2_1_14_1 e_1_2_1_37_1 e_1_2_1_58_1 e_1_2_1_18_1 e_1_2_1_40_1 e_1_2_1_23_1 e_1_2_1_46_1 e_1_2_1_61_1 e_1_2_1_21_1 e_1_2_1_44_1 e_1_2_1_27_1 e_1_2_1_25_1 e_1_2_1_48_1 e_1_2_1_29_1 Fielding Roy Thomas (e_1_2_1_24_1) 2000 Lyu Chenyang (e_1_2_1_42_1) 2023 Corradini Davide (e_1_2_1_20_1) 2022; 32 e_1_2_1_7_1 e_1_2_1_55_1 e_1_2_1_5_1 e_1_2_1_57_1 e_1_2_1_3_1 e_1_2_1_13_1 e_1_2_1_34_1 e_1_2_1_51_1 e_1_2_1_1_1 e_1_2_1_11_1 e_1_2_1_32_1 e_1_2_1_53_1 e_1_2_1_17_1 e_1_2_1_38_1 e_1_2_1_15_1 e_1_2_1_36_1 e_1_2_1_59_1 e_1_2_1_9_1 e_1_2_1_19_1 |
| References_xml | – reference: 2024. FuzzyWuzzy. https://github.com/seatgeek/fuzzywuzzy Accessed: 2024-07-04 – reference: Xintao Niu, Changhai Nie, Hareton Leung, Yu Lei, Xiaoyin Wang, Jiaxi Xu, and Yan Wang. 2020. An Interleaving Approach to Combinatorial Testing and Failure-Inducing Interaction Identification. IEEE Transactions on Software Engineering, 46, 6 (2020), 584–615. https://doi.org/10.1109/TSE.2018.2865772 10.1109/TSE.2018.2865772 – reference: Wu Biao, Tang Chaojing, and Zhang Bin. 2021. FFUZZ: A Fast Fuzzing Test Method for Stateful Network Protocol Implementation. In 2021 2nd International Conference on Computer Communication and Network Security (CCNS). 75–79. https://doi.org/10.1109/CCNS53852.2021.00023 10.1109/CCNS53852.2021.00023 – reference: 2024. Tcases. https://github.com/Cornutum/tcases Accessed: 2024-10-30 – reference: Alberto Martin-Lopez, Sergio Segura, and Antonio Ruiz-Cortés. 2019. Test coverage criteria for RESTful web APIs. In Proceedings of the 10th ACM SIGSOFT International Workshop on Automating TEST Case Design, Selection, and Evaluation (A-TEST 2019). Association for Computing Machinery, New York, NY, USA. 15–21. isbn:9781450368506 https://doi.org/10.1145/3340433.3342822 10.1145/3340433.3342822 – reference: Andrea Arcuri. 2018. An experience report on applying software testing academic results in industry: we need usable automated test generation. Empirical Softw. Engg., 23, 4 (2018), Aug., 1959–1981. issn:1382-3256 https://doi.org/10.1007/s10664-017-9570-9 10.1007/s10664-017-9570-9 – reference: Roy Thomas Fielding and Richard N. Taylor. 2000. Architectural styles and the design of network-based software architectures. Ph. D. Dissertation. isbn:0599871180 AAI9980887 – reference: Sergio Segura, José A. Parejo, Javier Troya, and Antonio Ruiz-Cortés. 2018. Metamorphic testing of RESTful web APIs. 882. isbn:9781450356381 https://doi.org/10.1145/3180155.3182528 10.1145/3180155.3182528 – reference: Myeongsoo Kim, Saurabh Sinha, and Alessandro Orso. 2023. Adaptive REST API Testing with Reinforcement Learning. IEEE Computer Society, 446–458. isbn:9798350329964 https://doi.org/10.1109/ASE56229.2023.00218 10.1109/ASE56229.2023.00218 – reference: Jiaxian Lin, Tianyu Li, Yang Chen, Guangsheng Wei, Jiadong Lin, Sen Zhang, and Hui Xu. 2023. foREST: A Tree-based Black-box Fuzzing Approach for RESTful APIs. IEEE Computer Society, 695–705. isbn:9798350315943 https://doi.org/10.1109/ISSRE59848.2023.00023 10.1109/ISSRE59848.2023.00023 – reference: Jinkun Lin, Shaowei Cai, Bing He, Yingjie Fu, Chuan Luo, and Qingwei Lin. 2021. FastCA: An Effective and Efficient Tool for Combinatorial Covering Array Generation. In 2021 IEEE/ACM 43rd International Conference on Software Engineering: Companion Proceedings (ICSE-Companion). 77–80. https://doi.org/10.1109/ICSE-Companion52605.2021.00040 10.1109/ICSE-Companion52605.2021.00040 – reference: Davide Corradini, Michele Pasqua, and Mariano Ceccato. 2023. Automated Black-Box Testing of Mass Assignment Vulnerabilities in RESTful APIs. In Proceedings of the 45th International Conference on Software Engineering (ICSE ’23). IEEE Press, 2553–2564. isbn:9781665457019 https://doi.org/10.1109/ICSE48619.2023.00213 10.1109/ICSE48619.2023.00213 – reference: Mark Nottingham and Erik Wilde. 2016. Problem Details for HTTP APIs. RFC 7807. https://doi.org/10.17487/RFC7807 10.17487/RFC7807 – reference: Zu-Ming Jiang, Jia-Ju Bai, and Zhendong Su. 2023. DynSQL: Stateful fuzzing for database management systems with complex and valid SQL query generation. In Proceedings of the 32nd USENIX Conference on Security Symposium (SEC ’23). USENIX Association, USA. Article 277, 17 pages. isbn:978-1-939133-37-3 – reference: Alberto Martin-Lopez, Sergio Segura, and Antonio Ruiz-Cortés. 2019. A Catalogue of Inter-parameter Dependencies in RESTful Web APIs. In Service-Oriented Computing: 17th International Conference, ICSOC 2019, Toulouse, France, October 28–31, 2019, Proceedings. Springer-Verlag, Berlin, Heidelberg. 399–414. isbn:978-3-030-33701-8 https://doi.org/10.1007/978-3-030-33702-5_31 10.1007/978-3-030-33702-5_31 – reference: Myeongsoo Kim, Qi Xin, Saurabh Sinha, and Alessandro Orso. 2022. Automated test generation for REST APIs: no time to rest yet. In Proceedings of the 31st ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA 2022). Association for Computing Machinery, New York, NY, USA. 289–301. isbn:9781450393799 https://doi.org/10.1145/3533767.3534401 10.1145/3533767.3534401 – reference: A. Giuliano Mirabella, Alberto Martin-Lopez, Sergio Segura, Luis Valencia-Cabrera, and Antonio Ruiz-Cortes. 2021. Deep Learning-Based Prediction of Test Input Validity for RESTful APIs. In 2021 IEEE/ACM Third International Workshop on Deep Learning for Testing and Testing for Deep Learning (DeepTest). IEEE, 9–16. isbn:978-1-66544-565-8 https://doi.org/10.1109/DeepTest52559.2021.00008 10.1109/DeepTest52559.2021.00008 – reference: SpringDoc Contributors. 2024. SpringDoc OpenAPI. https://springdoc.org/ Accessed: 2025-02-11 – reference: Myeongsoo Kim, Tyler Stennett, Dhruv Shah, Saurabh Sinha, and Alessandro Orso. 2024. Leveraging Large Language Models to Improve REST API Testing. In Proceedings of the 2024 ACM/IEEE 44th International Conference on Software Engineering: New Ideas and Emerging Results (ICSE-NIER’24). Association for Computing Machinery, New York, NY, USA. 37–41. isbn:9798400705007 https://doi.org/10.1145/3639476.3639769 10.1145/3639476.3639769 – reference: Mark Nottingham, Erik Wilde, and Sanjay Dalal. 2023. Problem Details for HTTP APIs. RFC 9457. https://doi.org/10.17487/RFC9457 10.17487/RFC9457 – reference: Van-Thuan Pham, Marcel Böhme, and Abhik Roychoudhury. 2020. AFLNET: A Greybox Fuzzer for Network Protocols. In 2020 IEEE 13th International Conference on Software Testing, Validation and Verification (ICST). 460–465. https://doi.org/10.1109/ICST46399.2020.00062 10.1109/ICST46399.2020.00062 – reference: D.R. Kuhn, D.R. Wallace, and A.M. Gallo. 2004. Software fault interactions and implications for software testing. IEEE Transactions on Software Engineering, 30, 6 (2004), 418–421. https://doi.org/10.1109/TSE.2004.24 10.1109/TSE.2004.24 – reference: Alberto Martin-Lopez, Sergio Segura, and Antonio Ruiz-Cortés. 2021. RESTest: automated black-box testing of RESTful web APIs. In Proceedings of the 30th ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA 2021). Association for Computing Machinery, New York, NY, USA. 682–685. isbn:9781450384599 https://doi.org/10.1145/3460319.3469082 10.1145/3460319.3469082 – reference: Man Zhang and Andrea Arcuri. 2023. Open Problems in Fuzzing RESTful APIs: A Comparison of Tools. ACM Trans. Softw. Eng. Methodol., 32, 6 (2023), Article 144, sep, 45 pages. issn:1049-331X https://doi.org/10.1145/3597205 10.1145/3597205 – reference: Emanuele Viglianisi, Michael Dallago, and Mariano Ceccato. 2020. RESTTESTGEN: Automated Black-Box Testing of RESTful APIs. In 2020 IEEE 13th International Conference on Software Testing, Validation and Verification (ICST). 142–152. issn:2159-4848 https://doi.org/10.1109/ICST46399.2020.00024 10.1109/ICST46399.2020.00024 – reference: 2025. Replication package. https://zenodo.org/records/14940931 Accessed: 2025-02-28 – reference: Henk Grent, Aleksei Akimov, and Maurício Aniche. 2021. Automatically Identifying Parameter Constraints in Complex Web APIs: A Case Study at Adyen. In 2021 IEEE/ACM 43rd International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP). 71–80. https://doi.org/10.1109/ICSE-SEIP52600.2021.00016 10.1109/ICSE-SEIP52600.2021.00016 – reference: Yi Liu, Yuekang Li, Gelei Deng, Yang Liu, Ruiyuan Wan, Runchao Wu, Dandan Ji, Shiheng Xu, and Minli Bao. 2022. Morest: model-based RESTful API testing with execution feedback. In Proceedings of the 44th International Conference on Software Engineering (ICSE ’22). Association for Computing Machinery, New York, NY, USA. 1406–1417. isbn:9781450392211 https://doi.org/10.1145/3510003.3510133 10.1145/3510003.3510133 – reference: 2024. The Official YAML Web Site. https://yaml.org/ Accessed: 2024-07-04 – reference: Huayao Wu, Lixin Xu, Xintao Niu, and Changhai Nie. 2022. Combinatorial testing of RESTful APIs. In Proceedings of the 44th International Conference on Software Engineering (ICSE ’22). Association for Computing Machinery, New York, NY, USA. 426–437. isbn:9781450392211 https://doi.org/10.1145/3510003.3510151 10.1145/3510003.3510151 – reference: 2024. YouTube Data API Specification. https://api.apis.guru/v2/specs/googleapis.com/youtube/v3/openapi.yaml Accessed: 2024-10-29 – reference: 2024. Dredd. https://github.com/apiaryio/dredd Accessed: 2024-10-30 – reference: Andrea Arcuri. 2019. RESTful API Automated Test Case Generation with EvoMaster. ACM Trans. Softw. Eng. Methodol., 28, 1 (2019), Article 3, jan, 37 pages. issn:1049-331X https://doi.org/10.1145/3293455 10.1145/3293455 – reference: 2024. PICT. https://github.com/microsoft/pict Accessed: 2024-07-04 – reference: Davide Corradini, Amedeo Zampieri, Michele Pasqua, Emanuele Viglianisi, Michael Dallago, and Mariano Ceccato. 2022. Automated black-box testing of nominal and error scenarios in RESTful APIs. Software Testing, Verification and Reliability, 32, 5 (2022), e1808. – reference: Hamza Ed-douibi, Javier Luis Cánovas Izquierdo, and Jordi Cabot. 2018. Automatic Generation of Test Cases for REST APIs: A Specification-Based Approach. 2018 IEEE 22nd International Enterprise Distributed Object Computing Conference (EDOC), 181–190. https://doi.org/10.1109/edoc.2018.00031 10.1109/edoc.2018.00031 – reference: Vaggelis Atlidakis, Patrice Godefroid, and Marina Polishchuk. 2019. RESTler: stateful REST API fuzzing. In Proceedings of the 41st International Conference on Software Engineering (ICSE ’19). IEEE Press, 748–758. https://doi.org/10.1109/ICSE.2019.00083 10.1109/ICSE.2019.00083 – reference: Zac Hatfield-Dodds and Dmitry Dygalo. 2022. Deriving semantics-aware fuzzers from web API schemas. In Proceedings of the ACM/IEEE 44th International Conference on Software Engineering: Companion Proceedings (ICSE ’22). Association for Computing Machinery, New York, NY, USA. 345–346. isbn:9781450392235 https://doi.org/10.1145/3510454.3528637 10.1145/3510454.3528637 – reference: Myeongsoo Kim, Davide Corradini, Saurabh Sinha, Alessandro Orso, Michele Pasqua, Rachel Tzoref-Brill, and Mariano Ceccato. 2023. Enhancing REST API Testing with NLP Techniques. In Proceedings of the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA 2023). Association for Computing Machinery, New York, NY, USA. 1232–1243. isbn:9798400702211 https://doi.org/10.1145/3597926.3598131 10.1145/3597926.3598131 – reference: Changhai Nie and Hareton Leung. 2011. A survey of combinatorial testing. ACM Comput. Surv., 43, 2 (2011), Article 11, Feb., 29 pages. issn:0360-0300 https://doi.org/10.1145/1883612.1883618 10.1145/1883612.1883618 – reference: S. Karlsson, A. Causevic, and D. Sundmark. 2020. QuickREST: Property-based Test Generation of OpenAPI-Described RESTful APIs. In 2020 IEEE 13th International Conference on Software Testing, Validation and Verification (ICST). IEEE Computer Society, Los Alamitos, CA, USA. 131–141. issn:2159-4848 https://doi.org/10.1109/ICST46399.2020.00023 10.1109/ICST46399.2020.00023 – reference: Dimitri Stallenberg, Mitchell Olsthoorn, and Annibale Panichella. 2022. Improving test case generation for REST APIs through hierarchical clustering. In Proceedings of the 36th IEEE/ACM International Conference on Automated Software Engineering (ASE ’21). IEEE Press, 117–128. isbn:9781665403375 https://doi.org/10.1109/ASE51524.2021.9678586 10.1109/ASE51524.2021.9678586 – reference: Patrice Godefroid, Bo-Yuan Huang, and Marina Polishchuk. 2020. Intelligent REST API data fuzzing. In Proceedings of the 28th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE 2020). Association for Computing Machinery, New York, NY, USA. 725–736. isbn:9781450370431 https://doi.org/10.1145/3368089.3409719 10.1145/3368089.3409719 – reference: Xinyi Wang, Paolo Arcaini, Tao Yue, and Shaukat Ali. 2024. QuCAT: A Combinatorial Testing Tool for Quantum Software. In Proceedings of the 38th IEEE/ACM International Conference on Automated Software Engineering (ASE ’23). IEEE Press, 2066–2069. isbn:9798350329964 https://doi.org/10.1109/ASE56229.2023.00062 10.1109/ASE56229.2023.00062 – reference: 2024. JSON. https://www.json.org/json-en.html Accessed: 2024-07-04 – reference: Adam Doupé, Ludovico Cavedon, Christopher Kruegel, and Giovanni Vigna. 2012. Enemy of the state: a state-aware black-box web vulnerability scanner. In Proceedings of the 21st USENIX Conference on Security Symposium (Security’12). USENIX Association, USA. 26. – reference: Saman Barakat, Ana Belén Sánchez, and Sergio Segura. 2023. IDLGen: Automated Code Generation for Inter-parameter Dependencies in Web APIs. In Service-Oriented Computing: 21st International Conference, ICSOC 2023, Rome, Italy, November 28 – December 1, 2023, Proceedings, Part I. Springer-Verlag, Berlin, Heidelberg. 153–168. isbn:978-3-031-48420-9 https://doi.org/10.1007/978-3-031-48421-6_11 10.1007/978-3-031-48421-6_11 – reference: Amid Golmohammadi, Man Zhang, and Andrea Arcuri. 2023. Testing RESTful APIs: A Survey. ACM Trans. Softw. Eng. Methodol., 33, 1 (2023), Article 27, nov, 41 pages. issn:1049-331X https://doi.org/10.1145/3617175 10.1145/3617175 – reference: Swaroopa Dola, Rory McDaniel, Matthew B. Dwyer, and Mary Lou Soffa. 2024. CIT4DNN: Generating Diverse and Rare Inputs for Neural Networks Using Latent Space Combinatorial Testing. In Proceedings of the IEEE/ACM 46th International Conference on Software Engineering (ICSE ’24). Association for Computing Machinery, New York, NY, USA. Article 118, 13 pages. isbn:9798400702174 https://doi.org/10.1145/3597503.3639106 10.1145/3597503.3639106 – reference: Postman API Evangelist. 2024. Postman to OpenAPI Collection. https://www.postman.com/api-evangelist/artificial-intelligence/collection/txy0rdd/postman-to-openapi Accessed: 2025-02-11 – reference: Alberto Martin-Lopez, Sergio Segura, Carlos Müller, and Antonio Ruiz-Cortés. 2022. Specification and Automated Analysis of Inter-Parameter Dependencies in Web APIs. IEEE Transactions on Services Computing, 15, 4 (2022), 2342–2355. https://doi.org/10.1109/TSC.2021.3050610 10.1109/TSC.2021.3050610 – reference: Tri Le, Thien Tran, Duy Cao, Vy Le, Tien N. Nguyen, and Vu Nguyen. 2024. KAT: Dependency-Aware Automated API Testing with Large Language Models. In 2024 IEEE Conference on Software Testing, Verification and Validation (ICST). IEEE Computer Society, Los Alamitos, CA, USA. 82–92. issn:2159-4848 https://doi.org/10.1109/ICST60714.2024.00017 10.1109/ICST60714.2024.00017 – reference: Manuel Leithner, Andrea Bombarda, Michael Wagner, Angelo Gargantini, and Dimitris E. Simos. 2024. State of the CArt: evaluating covering array generators at scale. Int. J. Softw. Tools Technol. Transf., 26, 3 (2024), May, 301–326. issn:1433-2779 https://doi.org/10.1007/s10009-024-00745-2 10.1007/s10009-024-00745-2 – reference: Chenyang Lyu, Jiacheng Xu, Shouling Ji, Xuhong Zhang, Qinying Wang, Binbin Zhao, Gaoning Pan, Wei Cao, Peng Chen, and Raheem Beyah. 2023. MINER: a hybrid data-driven approach for REST API fuzzing. In Proceedings of the 32nd USENIX Conference on Security Symposium (SEC ’23). USENIX Association, USA. Article 253, 18 pages. isbn:978-1-939133-37-3 – reference: Sunny Shree, Krishna Khadka, Yu Lei, Raghu N. Kacker, and D. Richard Kuhn. 2024. Constructing Surrogate Models in Machine Learning Using Combinatorial Testing and Active Learning. In Proceedings of the 39th IEEE/ACM International Conference on Automated Software Engineering (ASE ’24). Association for Computing Machinery, New York, NY, USA. 1645–1654. isbn:9798400712487 https://doi.org/10.1145/3691620.3695532 10.1145/3691620.3695532 – reference: 2024. Built-in String Formats of OpenAPI. https://swagger.io/docs/specification/data-models/data-types/##string Accessed: 2024-07-02 – reference: RobBagby. 2023. Web API Implementation - Best Practices for Cloud Applications. https://learn.microsoft.com/en-us/azure/architecture/best-practices/api-implementation. – reference: Juan C. Alonso. 2021. Automated generation of realistic test inputs for web APIs. In Proceedings of the 29th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE 2021). Association for Computing Machinery, New York, NY, USA. 1666–1668. isbn:9781450385626 https://doi.org/10.1145/3468264.3473491 10.1145/3468264.3473491 – reference: 2024. JaCoCo. https://www.eclemma.org/jacoco/ Accessed: 2024-07-02 – reference: 2024. MITMProxy. https://mitmproxy.org/ Accessed: 2024-07-04 – reference: 2024. OpenAPI Specification - Version 3.1.0 | Swagger. https://swagger.io/specification/ Accessed: 2024-07-02 – ident: e_1_2_1_60_1 doi: 10.1109/ASE56229.2023.00062 – ident: e_1_2_1_46_1 doi: 10.1145/3460319.3469082 – ident: e_1_2_1_43_1 doi: 10.1109/TSC.2021.3050610 – volume-title: Taylor year: 2000 ident: e_1_2_1_24_1 – ident: e_1_2_1_48_1 doi: 10.1145/1883612.1883618 – ident: e_1_2_1_34_1 doi: 10.1145/3639476.3639769 – ident: e_1_2_1_35_1 doi: 10.1145/3533767.3534401 – ident: e_1_2_1_47_1 doi: 10.1109/DeepTest52559.2021.00008 – ident: e_1_2_1_58_1 doi: 10.1109/ASE51524.2021.9678586 – ident: e_1_2_1_39_1 doi: 10.1109/ICSE-Companion52605.2021.00040 – ident: e_1_2_1_18_1 doi: 10.1109/CCNS53852.2021.00023 – ident: e_1_2_1_21_1 doi: 10.1145/3597503.3639106 – ident: e_1_2_1_31_1 doi: 10.1109/ICST46399.2020.00023 – ident: e_1_2_1_37_1 doi: 10.1109/ICST60714.2024.00017 – ident: e_1_2_1_41_1 doi: 10.1145/3510003.3510133 – ident: e_1_2_1_19_1 doi: 10.1109/ICSE48619.2023.00213 – ident: e_1_2_1_6_1 doi: 10.53414/UIJES.2024.4.4.17 – ident: e_1_2_1_33_1 doi: 10.1109/ASE56229.2023.00218 – ident: e_1_2_1_55_1 doi: 10.1145/3180155.3182528 – ident: e_1_2_1_38_1 doi: 10.1007/s10009-024-00745-2 – ident: e_1_2_1_45_1 doi: 10.1145/3340433.3342822 – ident: e_1_2_1_12_1 – ident: e_1_2_1_57_1 – ident: e_1_2_1_4_1 – ident: e_1_2_1_44_1 doi: 10.1007/978-3-030-33702-5_31 – ident: e_1_2_1_53_1 – ident: e_1_2_1_25_1 doi: 10.1145/3368089.3409719 – ident: e_1_2_1_32_1 doi: 10.1145/3597926.3598131 – ident: e_1_2_1_8_1 – ident: e_1_2_1_2_1 – ident: e_1_2_1_5_1 – ident: e_1_2_1_10_1 – ident: e_1_2_1_15_1 doi: 10.1145/3293455 – ident: e_1_2_1_62_1 doi: 10.1145/3597205 – ident: e_1_2_1_7_1 – ident: e_1_2_1_28_1 doi: 10.1145/3510454.3528637 – ident: e_1_2_1_52_1 doi: 10.1109/ICST46399.2020.00062 – ident: e_1_2_1_14_1 doi: 10.1007/s10664-017-9570-9 – ident: e_1_2_1_13_1 doi: 10.1145/3468264.3473491 – volume-title: Proceedings of the 21st USENIX Conference on Security Symposium (Security’12) year: 2012 ident: e_1_2_1_22_1 – ident: e_1_2_1_59_1 doi: 10.1109/ICST46399.2020.00024 – ident: e_1_2_1_26_1 doi: 10.1145/3617175 – ident: e_1_2_1_49_1 doi: 10.1109/TSE.2018.2865772 – ident: e_1_2_1_54_1 – ident: e_1_2_1_23_1 doi: 10.1109/edoc.2018.00031 – ident: e_1_2_1_1_1 – ident: e_1_2_1_40_1 doi: 10.1109/ISSRE59848.2023.00023 – ident: e_1_2_1_56_1 doi: 10.1145/3691620.3695532 – ident: e_1_2_1_29_1 doi: 10.1145/3510454.3528637 – ident: e_1_2_1_27_1 doi: 10.1109/ICSE-SEIP52600.2021.00016 – ident: e_1_2_1_51_1 doi: 10.17487/RFC9457 – ident: e_1_2_1_16_1 doi: 10.1109/ICSE.2019.00083 – ident: e_1_2_1_3_1 – ident: e_1_2_1_36_1 doi: 10.1109/TSE.2004.24 – ident: e_1_2_1_11_1 – ident: e_1_2_1_50_1 doi: 10.17487/RFC7807 – ident: e_1_2_1_17_1 doi: 10.1007/978-3-031-48421-6_11 – volume-title: Proceedings of the 32nd USENIX Conference on Security Symposium (SEC ’23) year: 2023 ident: e_1_2_1_42_1 – ident: e_1_2_1_9_1 – volume-title: Proceedings of the 32nd USENIX Conference on Security Symposium (SEC ’23) year: 2023 ident: e_1_2_1_30_1 – ident: e_1_2_1_61_1 doi: 10.1145/3510003.3510151 – volume: 32 start-page: e1808 year: 2022 ident: e_1_2_1_20_1 article-title: Automated black-box testing of nominal and error scenarios in RESTful APIs publication-title: Software Testing, Verification and Reliability doi: 10.1002/stvr.1808 |
| SSID | ssj0002991170 |
| Score | 2.295198 |
| Snippet | REST APIs are essential for building modern enterprise systems, but effectively testing them remains challenging, particularly due to difficulties in inferring... |
| SourceID | crossref acm |
| SourceType | Index Database Publisher |
| StartPage | 1978 |
| SubjectTerms | Software and its engineering Software testing and debugging |
| SubjectTermsDisplay | Software and its engineering -- Software testing and debugging |
| Title | Effective REST APIs Testing with Error Message Analysis |
| URI | https://dl.acm.org/doi/10.1145/3728964 |
| Volume | 2 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVHPJ databaseName: ROAD: Directory of Open Access Scholarly Resources (ISSN International Center) customDbUrl: eissn: 2994-970X dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0002991170 issn: 2994-970X databaseCode: M~E dateStart: 20240101 isFulltext: true titleUrlDefault: https://road.issn.org providerName: ISSN International Centre |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1LS8NAEF7q4-DFt_hmD94k2GSb17GIogdLwYDFi2yyu1rQtDRW68Xf7kx2N02loB68hLDJhjDzZXZmM_MNISctrykyFbuOTDkEKC5vORzsoAOmz00jpkIW8LLZRNjpRL1e3G00JrYW5u05zPNoMomH_6pqGANlY-nsH9RdPRQG4ByUDkdQOxx_pXjNR4wJQSDc5LTdvS5OE-TSsLuuF6PRAMl7Cswpq1hJ6l5qt1rVCptD0D6_wf8KBVjtd0wWk1MeQ6uz3lgH-ZN-Bbi7cuhqzD_4YPqzqjR0908y_xjPzk0GZTr_Y30rwvMxZcqr7U56yDMch82eXlzmjBmT69WQdX17m7RrJtSNdU8fsxxjKdF8U99CVgwWQsSoedBnybS_LXJV6qEuxPYfzMQFsuSFfozJgDef0905eGtsyYOdCe3764prnHtm5qJDk73UHJqaZ5Ksk1UTUtC2hsIGach8k6zZdh3UWO8tElbIoIgMisigBhkUkUFLZFCDDGqRsU2Sy4vk_MoxfTMcDu6vw-NUQdTvC2TaZ14mXIFc1JliSjIRiSbyFQXc5R6PVNMXgYoynqYCgv80iFzFdshiPsjlLqHSB4dYpqEKsHhdwMfLYoh5ZcACiJOjbI9sggQehpoYxcp0j1ArkerSN7Hv_3zLAVmZYuyQLL6OxvKILGdvr_1idFyq6wsViloO |
| linkProvider | ISSN International Centre |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Effective+REST+APIs+Testing+with+Error+Message+Analysis&rft.jtitle=Proceedings+of+the+ACM+on+software+engineering&rft.au=Xu%2C+Lixin&rft.au=Wu%2C+Huayao&rft.au=Pan%2C+Zhenyu&rft.au=Xu%2C+Tongtong&rft.date=2025-06-22&rft.issn=2994-970X&rft.eissn=2994-970X&rft.volume=2&rft.issue=ISSTA&rft.spage=1978&rft.epage=2000&rft_id=info:doi/10.1145%2F3728964&rft.externalDBID=n%2Fa&rft.externalDocID=10_1145_3728964 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2994-970X&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2994-970X&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2994-970X&client=summon |