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Language-independent information flow tracking engine for program comprehension tools

Language-independent information flow tracking engine for program comprehension tools
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Conference Paper: ICPC'17, May, 2017

Program comprehension tools are often developed for a specific programming language. Developing such a tool from scratch requires significant effort. In this paper, we report on our experience developing a language-independent framework that enables the creation of program comprehension tools, specifically tools gathering insight from deep dynamic analysis, with little effort. Our framework is language independent, because it is built on top of Truffle, an open-source platform, developed in Oracle Labs, for implementing dynamic languages in the form of AST interpreters. Our framework supports the creation of a diverse variety of program comprehension techniques, such as query, program slicing, and back-in-time debugging, because it is centered around a powerful information-flow tracking engine.

Tools developed with our framework get access to the information-flow through a program execution. While it is possible to develop similarly powerful tools without our framework, for example by tracking information-flow through bytecode instrumentation, our approach leads to information that is closer to source code constructs, thus more comprehensible by the user.

To demonstrate the effectiveness of our framework, we applied it to two of Truffle-based languages namely Simple Language and TruffleRuby, and we distill our experience into guidelines for developers of other Truffle-based languages who want to develop program comprehension tools for their language.

@inproceedings{Azadmanesh:2017:LIF:3101414.3101460, author = {Azadmanesh, Mohammad Reza and Hauswirth, Matthias and Van De Vanter, Michael L.}, title = {Language-independent Information Flow Tracking Engine for Program Comprehension Tools}, booktitle = {Proceedings of the 25th International Conference on Program Comprehension}, series = {ICPC '17}, year = {2017}, isbn = {978-1-5386-0535-6}, location = {Buenos Aires, Argentina}, pages = {346--355}, numpages = {10}, url = {https://doi.org/10.1109/ICPC.2017.5}, doi = {10.1109/ICPC.2017.5}, acmid = {3101460}, publisher = {IEEE Press}, address = {Piscataway, NJ, USA}, }