2008•Unpublished venueRequires access

Implementing Java modeling language contracts with AspectJ

Henrique Rebêlo, Sérgio Soares, Ricardo Lima, Leopoldo Pires Ferreira, Márcio Cornélio

Open publisher page 24 citations

Abstract

The Java Modeling Language (JML) is a behavioral interface specification language (BISL) designed for Java. It was developed to improve functional software correctness of Java applications. However, instrumented object program generated by the JML compiler use the Java reflection mechanism and data structures not supported by Java ME applications. To deal with this limitation, we propose the use of AspectJ to implement a new JML compiler, which generates an instrumented bytecode compliant with both Java SE and Java ME applications. The paper includes a comparative study to demonstrate the quality of the final code generated by our compiler. The size of the code is compared against the code generated by an existent JML compiler. Moreover, we evaluate the amount of additional code required to implement the JML assertions in Java applications. Results indicate that the overhead in code size produced by our compiler is very small, which is essential for Java ME applications.

About this research paper

What this paper is about

The Java Modeling Language (JML) is a behavioral interface specification language (BISL) designed for Java. It was developed to improve functional software correctness of Java applications. However, instrumented object program generated by the JML compiler use the Java reflection mechanism and data structures not supported by Java ME applications. To deal with this limitation, we propose the use of AspectJ to implement a new JML compiler, which generates an instrumented bytecode compliant with both Java SE and Java ME applications. The paper includes a comparative study to demonstrate the quality of the final code generated by our compiler. The size of the code is compared against the code generated by an existent JML compiler. Moreover, we evaluate the amount of additional code required to implement the JML assertions in Java applications. Results indicate that the overhead in code size produced by our compiler is very small, which is essential for Java ME applications.

Why it matters

OpenAlex reports 24 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

The Java Modeling Language (JML) is a behavioral interface specification language (BISL) designed for Java. It was developed to improve functional software correctness of Java applications. However, instrumented object program generated by the JML compiler use the Java reflection mechanism and data structures not supported by Java ME applications. To deal with this limitation, we propose the use of AspectJ to implement a new JML compiler, which generates an instrumented bytecode compliant with both Java SE and Java ME applications. The paper includes a comparative study to demonstrate the quality of the final code generated by our compiler. The size of the code is compared against the code generated by an existent JML compiler. Moreover, we evaluate the amount of additional code required to implement the JML assertions in Java applications. Results indicate that the overhead in code size produced by our compiler is very small, which is essential for Java ME applications.

Key concepts: Computer science, AspectJ, Java Modeling Language, Programming language, Java, Java annotation, Java bytecode, Generics in Java

Related papers

Back to paper searchBrowse research topicsOriginal source
Implementing Java modeling language contracts with AspectJ — Research Paper | ScholarLens