A Comparative Study of Code Query Technologies
In this comparative study by the Software Improvement Group, the Universidade do Minho, and Utrecht University seven technologies for querying program code were evaluated against 12 criteria.
A Comparative Study of Code Query Technologies
By Tiago L. Alves (SIG & Universidade do Minho), Jurriaan Hage (Utrecht University),
Peter Rademaker (Utrecht University).
Published in: 11th IEEE International Working Conference on Source Code Analysis and Manipulation, Williamsburg, VA, USA.
By Tiago L. Alves (SIG & Universidade do Minho), Jurriaan Hage (Utrecht University),
Peter Rademaker (Utrecht University).
Published in: 11th IEEE International Working Conference on Source Code Analysis and Manipulation, Williamsburg, VA, USA.
Abstract:
When analyzing software systems we face the challenge of how to implement a particular analysis for different programming languages. A solution for this problem is to write a single analysis using a code query language, abstracting from the specificities of languages being analyzed. Over the past ten years many code query technologies have been developed, based on different formalisms. Each technology comes with its own query language and set of features.
To determine the state of the art of code querying we compare the languages and tools for seven code query technologies: Grok, Rscript, JRelCal, SemmleCode, JGraLab, CrocoPat and JTransformer. The specification of a package stability metric is used as a running example to compare the languages. The comparison involves twelve criteria, some of which are concerned with properties of the query language (paradigm, types, parametrization, polymorphism, modularity, and libraries), and some of which are concerned with the tool itself (output formats, interactive interface, API support, interchange formats, extraction support, and licensing). We contextualize the criteria in two usage scenarios: interactive and tool integration. We conclude that there is no particularly weak or dominant tool. As important improvement points, we identify the lack of library mechanisms, interchange formats, and possibilities for integration with source code extractors.
When analyzing software systems we face the challenge of how to implement a particular analysis for different programming languages. A solution for this problem is to write a single analysis using a code query language, abstracting from the specificities of languages being analyzed. Over the past ten years many code query technologies have been developed, based on different formalisms. Each technology comes with its own query language and set of features.
To determine the state of the art of code querying we compare the languages and tools for seven code query technologies: Grok, Rscript, JRelCal, SemmleCode, JGraLab, CrocoPat and JTransformer. The specification of a package stability metric is used as a running example to compare the languages. The comparison involves twelve criteria, some of which are concerned with properties of the query language (paradigm, types, parametrization, polymorphism, modularity, and libraries), and some of which are concerned with the tool itself (output formats, interactive interface, API support, interchange formats, extraction support, and licensing). We contextualize the criteria in two usage scenarios: interactive and tool integration. We conclude that there is no particularly weak or dominant tool. As important improvement points, we identify the lack of library mechanisms, interchange formats, and possibilities for integration with source code extractors.
Download publication:
A Comparative Study of Code Query Technologies
Publisher website:
11th IEEE International Working Conference on Source Code Analysis and Manipulation
A Comparative Study of Code Query Technologies
Publisher website:
11th IEEE International Working Conference on Source Code Analysis and Manipulation