Diego Clerissi;Giovanni Denaro;Marco Mobilio;Leonardo Mariani
{"title":"DBINPUTS:利用持久性数据改进图形用户界面自动测试","authors":"Diego Clerissi;Giovanni Denaro;Marco Mobilio;Leonardo Mariani","doi":"10.1109/TSE.2024.3439002","DOIUrl":null,"url":null,"abstract":"The generation of syntactically and semantically valid input data, able to exercise functionalities imposing constraints on the validity of the inputs, is a key challenge in automatic GUI (Graphical User Interface) testing. Existing test case generation techniques often rely on manually curated catalogs of values, although they might require significant effort to be created and maintained, and could hardly scale to applications with several input forms. Alternatively, it is possible to extract values from external data sources, such as the Web or publicly available knowledge bases. However, external sources are unlikely to provide the domain-specific and application-specific data that are often required to thoroughly exercise applications. This paper proposes \n<sc>DBInputs</small>\n, a novel approach that automatically identifies domain-specific and application-specific inputs to effectively fulfill the validity constraints present in the tested GUI screens. The approach exploits syntactic and semantic similarities between the identifiers of the input fields shown on GUI screens and those of the tables of the target GUI application database, and extracts valid inputs from such database, automatically resolving the mismatch between the user interface and the database schema. \n<sc>DBInputs</small>\n can properly cope with system testing and maintenance testing efforts, since databases are naturally and inexpensively available in those phases. Our experiments with 4 Web applications and 11 Mobile apps provide evidence that \n<sc>DBInputs</small>\n can outperform techniques like random input selection and \n<sc>Link</small>\n, a competing approach for searching inputs from knowledge bases, in both Web and Mobile domains.","PeriodicalId":13324,"journal":{"name":"IEEE Transactions on Software Engineering","volume":"50 9","pages":"2412-2436"},"PeriodicalIF":6.5000,"publicationDate":"2024-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10624678","citationCount":"0","resultStr":"{\"title\":\"DBInputs: Exploiting Persistent Data to Improve Automated GUI Testing\",\"authors\":\"Diego Clerissi;Giovanni Denaro;Marco Mobilio;Leonardo Mariani\",\"doi\":\"10.1109/TSE.2024.3439002\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The generation of syntactically and semantically valid input data, able to exercise functionalities imposing constraints on the validity of the inputs, is a key challenge in automatic GUI (Graphical User Interface) testing. Existing test case generation techniques often rely on manually curated catalogs of values, although they might require significant effort to be created and maintained, and could hardly scale to applications with several input forms. Alternatively, it is possible to extract values from external data sources, such as the Web or publicly available knowledge bases. However, external sources are unlikely to provide the domain-specific and application-specific data that are often required to thoroughly exercise applications. This paper proposes \\n<sc>DBInputs</small>\\n, a novel approach that automatically identifies domain-specific and application-specific inputs to effectively fulfill the validity constraints present in the tested GUI screens. The approach exploits syntactic and semantic similarities between the identifiers of the input fields shown on GUI screens and those of the tables of the target GUI application database, and extracts valid inputs from such database, automatically resolving the mismatch between the user interface and the database schema. \\n<sc>DBInputs</small>\\n can properly cope with system testing and maintenance testing efforts, since databases are naturally and inexpensively available in those phases. Our experiments with 4 Web applications and 11 Mobile apps provide evidence that \\n<sc>DBInputs</small>\\n can outperform techniques like random input selection and \\n<sc>Link</small>\\n, a competing approach for searching inputs from knowledge bases, in both Web and Mobile domains.\",\"PeriodicalId\":13324,\"journal\":{\"name\":\"IEEE Transactions on Software Engineering\",\"volume\":\"50 9\",\"pages\":\"2412-2436\"},\"PeriodicalIF\":6.5000,\"publicationDate\":\"2024-08-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10624678\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Software Engineering\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10624678/\",\"RegionNum\":1,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, SOFTWARE ENGINEERING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Software Engineering","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10624678/","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
DBInputs: Exploiting Persistent Data to Improve Automated GUI Testing
The generation of syntactically and semantically valid input data, able to exercise functionalities imposing constraints on the validity of the inputs, is a key challenge in automatic GUI (Graphical User Interface) testing. Existing test case generation techniques often rely on manually curated catalogs of values, although they might require significant effort to be created and maintained, and could hardly scale to applications with several input forms. Alternatively, it is possible to extract values from external data sources, such as the Web or publicly available knowledge bases. However, external sources are unlikely to provide the domain-specific and application-specific data that are often required to thoroughly exercise applications. This paper proposes
DBInputs
, a novel approach that automatically identifies domain-specific and application-specific inputs to effectively fulfill the validity constraints present in the tested GUI screens. The approach exploits syntactic and semantic similarities between the identifiers of the input fields shown on GUI screens and those of the tables of the target GUI application database, and extracts valid inputs from such database, automatically resolving the mismatch between the user interface and the database schema.
DBInputs
can properly cope with system testing and maintenance testing efforts, since databases are naturally and inexpensively available in those phases. Our experiments with 4 Web applications and 11 Mobile apps provide evidence that
DBInputs
can outperform techniques like random input selection and
Link
, a competing approach for searching inputs from knowledge bases, in both Web and Mobile domains.
期刊介绍:
IEEE Transactions on Software Engineering seeks contributions comprising well-defined theoretical results and empirical studies with potential impacts on software construction, analysis, or management. The scope of this Transactions extends from fundamental mechanisms to the development of principles and their application in specific environments. Specific topic areas include:
a) Development and maintenance methods and models: Techniques and principles for specifying, designing, and implementing software systems, encompassing notations and process models.
b) Assessment methods: Software tests, validation, reliability models, test and diagnosis procedures, software redundancy, design for error control, and measurements and evaluation of process and product aspects.
c) Software project management: Productivity factors, cost models, schedule and organizational issues, and standards.
d) Tools and environments: Specific tools, integrated tool environments, associated architectures, databases, and parallel and distributed processing issues.
e) System issues: Hardware-software trade-offs.
f) State-of-the-art surveys: Syntheses and comprehensive reviews of the historical development within specific areas of interest.