While industrial-strength static analysis over large, real-world codebases has become commonplace, so too have difficult-to-analyze language constructs, large libraries, and popular frameworks. These features make constructing and evaluating a novel, sound analysis painful, error-prone, and tedious. We motivate the need for research to address these issues by highlighting some of the many challenges faced by static analysis developers in today's software ecosystem. We then propose our short- and long-term research agenda to make static analysis over modern software less burdensome.
@InProceedings{toman_et_al:LIPIcs.SNAPL.2017.18, author = {Toman, John and Grossman, Dan}, title = {{Taming the Static Analysis Beast}}, booktitle = {2nd Summit on Advances in Programming Languages (SNAPL 2017)}, pages = {18:1--18:14}, series = {Leibniz International Proceedings in Informatics (LIPIcs)}, ISBN = {978-3-95977-032-3}, ISSN = {1868-8969}, year = {2017}, volume = {71}, editor = {Lerner, Benjamin S. and Bod{\'\i}k, Rastislav and Krishnamurthi, Shriram}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SNAPL.2017.18}, URN = {urn:nbn:de:0030-drops-71213}, doi = {10.4230/LIPIcs.SNAPL.2017.18}, annote = {Keywords: static analysis, frameworks, api knowledge, library specifications} }
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