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[null,"1.","Record Nr.",null,"UNISA996472066403316"]
[null,null,"Titolo",null,"Software quality, the next big thing in software engineering and quality : 14th international conference on software quality, SWQD 2022, Vienna, Austria, May 17-19, 2022 : proceedings / / edited by Daniel Mendez [and four others]"]
[null,null,"Pubbl/distr/stampa",null,"Cham, Switzerland : , : Springer, , [2022]"]
[{"$nulls":4},"©2022"]
[null,null,"ISBN",null,"3-031-04115-1"]
[null,null,"Descrizione fisica",null,"1 online resource (111 pages)"]
[null,null,"Collana",null,"Lecture Notes in Business Information Processing ; ; v.439"]
[null,null,"Disciplina",null,"005.1"]
[null,null,"Soggetti",null,"Computer software - Development"]
[{"$nulls":4},"Computer software - Quality control"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"Intro -- Message from the General Chair -- Message from the Scientific Program Chairs -- Organization -- Contents -- Invited Papers -- Continuous Software Engineering in the Wild -- 1 Introduction -- 2 Continuous Software Engineering in a Nutshell -- 3 Challenges and Future Needs -- 4 Conclusions -- References -- Motivations for and Benefits of Adopting the Test Maturity Model integration (TMMi) -- 1 Introduction -- 2 A Brief Overview of TMMi -- 3 Reasons (Motivations) for Adopting TMMi -- 4 Benefits of Adopting TMMi -- 5 Conclusion -- References -- AI in Software Engineering -- Automated Code Review Comment Classification to Improve Modern Code Reviews -- 1 Introduction -- 2 Related Work -- 3 CommentBERT - Classifying Code-Review Comments -- 3.1 Classifying Comments According to Their Focus -- 3.2 Training BERT for Code-Review Comments -- 3.3 Example of Application of the Taxonomy -- 4 Research Design -- 4.1 Research Questions -- 4.2 Datasets -- 4.3 Model Validation -- 5 Results -- 6 Discussion -- 7 Conclusions -- References -- A Preliminary Study on Using Text- and Image-Based Machine Learning to Predict Software Maintainability -- 1 Motivation -- 2 Experimental Design -- 2.1 Dataset -- 2.2 Architectures and Algorithms -- 2.3 Training and Evaluation -- 2.4 Preprocessing for Text-Based Prediction -- 2.5 Preprocessing for Image-Based Prediction -- 2.6 Experiment Execution -- 3 Experiment Results -- 3.1 Text-Based Classification -- "]
[{"$nulls":4},"3.2 Image-Based Classification -- 3.3 Interpretation -- 4 Discussion -- 4.1 Threats to Validity -- 4.2 Future Work -- 5 Related Work -- 6 Conclusion -- References -- Quality Assurance for Software-Intensive Systems -- Specification of Passive Test Cases Using an Improved T-EARS Language -- 1 Introduction -- 2 Background -- 2.1 Passive Testing -- 2.2 Guarded Assertions -- 2.3 Easy Approach to Requirements Syntax (EARS)."]
[{"$nulls":4},"2.4 The Ohm Grammar Language -- 3 Method -- 4 Result: The Updated T-EARS Language -- 4.1 Keyword Terminals -- 4.2 Structural Elements -- 4.3 Basic Data Types -- 4.4 Signals Data Type -- 4.5 Intervals Data Type -- 4.6 Events Data Type -- 4.7 Boolean Expressions -- 4.8 Guarded Assertion Rules -- 4.9 Miscellaneous Modifiers -- 4.10 Timing Considerations -- 4.11 General Structure of a T-EARS Test Case -- 5 Discussion on T-EARS Improvement -- 6 Related Work -- 7 Conclusion and Future Work -- References -- A Quality Model and Checklists for Reviewing Automotive Test Case Specifications -- 1 Introduction -- 2 Related Work -- 3 Developing a Quality Model for Automotive Test Case Specifications -- 3.1 Application of the Goal Question Metric (GQM) Approach -- 3.2 Automotive Test Case Specifications Quality Model -- 4 Review of Automotive Test Case Specifications -- 5 Evaluation -- 6 Conclusion and Future Work -- References -- Author Index."]