Affiliation:
1. 8748 10 Sideroad Adjala, RR 1, Palgrave, ON, Canada L0N 1P0
Abstract
This paper describes AnnaBot, one of the first tools to verify correct use of Annotation-based metadata in the Java
programming language. These Annotations are a standard Java 5 mechanism used to attach metadata to types, methods, or fields without using an external configuration file. A binary representation of the Annotation becomes part of the compiled “.class” file,
for inspection by another component or library at runtime. Java Annotations were introduced into the Java language in 2004 and have become widely used in recent years due to their introduction in the Java Enterprise Edition 5, the Hibernate object-relational mapping API, the Spring Framework, and elsewhere. Despite that, mainstream development tools have not yet produced a widely-used verification tool to confirm correct configuration and placement of annotations external to the particular runtime component. While most of the examples in this paper use the Java Persistence API, AnnaBot is capable of verifying anyannotation-based API for which “claims”—description of annotation
usage—are available. These claims can be written in Java or using a proposed Domain-Specific Language, which has been designed and a parser (but not the code generator) have been written.
Cited by
8 articles.
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1. Using Graph Neural Network to Analyse and Detect Annotation Misuse in Java Code;Lecture Notes in Computer Science;2024
2. Mining Annotation Usage Rules: A Case Study with MicroProfile;2022 IEEE International Conference on Software Maintenance and Evolution (ICSME);2022-10
3. DeepAnna: Deep Learning based Java Annotation Recommendation and Misuse Detection;2022 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER);2022-03
4. Mutating code annotations: An empirical evaluation on Java and C# programs;Science of Computer Programming;2020-06
5. Mutation Operators for Code Annotations;Proceedings of the III Brazilian Symposium on Systematic and Automated Software Testing - SAST '18;2018