| Title | MAF: A Framework for Modular Static Analysis of Higher-Order Languages |
| Publication Type | Conference Paper |
| Year of Publication | 2020 |
| Authors | Van Es, Noah, Van der Plas, Jens, Stiévenart, Quentin, De Roover, Coen |
| Conference Name | 2020 IEEE 20th International Working Conference on Source Code Analysis and Manipulation (SCAM) |
| Date Published | sep |
| Keywords | best practices, composability, Conferences, Debugging, Dynamic scheduling, Human Behavior, modular analysis, Performance analysis, pubcrawl, Resiliency, static analysis, static code analysis, static program analysis, visualization |
| Abstract | A modular static analysis decomposes a program's analysis into analyses of its parts, or components. An intercomponent analysis instructs an intra-component analysis to analyse each component independently of the others. Additional analyses are scheduled for newly discovered components, and for dependent components that need to account for newly discovered component information. Modular static analyses are scalable, can be tuned to a high precision, and support the analysis of programs that are highly dynamic, featuring e.g., higher-order functions or dynamically allocated processes.In this paper, we present the engineering aspects of MAF, a static analysis framework for implementing modular analyses for higher-order languages. For any such modular analysis, the framework provides a reusable inter-component analysis and it suffices to implement its intra-component analysis. The intracomponent analysis can be composed from several interdependent and reusable Scala traits. This design facilitates changing the analysed language, as well as the analysis precision with minimal effort. We illustrate the use of MAF through its instantiation for several different analyses of Scheme programs. |
| DOI | 10.1109/SCAM51674.2020.00009 |
| Citation Key | van_es_maf_2020 |
MAF: A Framework for Modular Static Analysis of Higher-Order Languages