Easing Maintenance of Academic Static Analyzers

Fuente: arXiv
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Hauptverfasser: Monat, Raphaël, Ouadjaout, Abdelraouf, Miné, Antoine
Format: Preprint
Veröffentlicht: 2024
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author Monat, Raphaël
Ouadjaout, Abdelraouf
Miné, Antoine
author_facet Monat, Raphaël
Ouadjaout, Abdelraouf
Miné, Antoine
contents Academic research in static analysis produces software implementations. These implementations are time-consuming to develop and some need to be maintained in order to enable building further research upon the implementation. While necessary, these processes can be quickly challenging. This article documents the tools and techniques we have come up with to simplify the maintenance of Mopsa since 2017. Mopsa is a static analysis platform that aims at being sound. First, we describe an automated way to measure precision that does not require any baseline of true bugs obtained by manually inspecting the results. Further, it improves transparency of the analysis, and helps discovering regressions during continuous integration. Second, we have taken inspiration from standard tools observing the concrete execution of a program to design custom tools observing the abstract execution of the analyzed program itself, such as abstract debuggers and profilers. Finally, we report on some cases of automated testcase reduction.
format Preprint
id arxiv_https___arxiv_org_abs_2407_12499
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Easing Maintenance of Academic Static Analyzers
Monat, Raphaël
Ouadjaout, Abdelraouf
Miné, Antoine
Programming Languages
Software Engineering
Academic research in static analysis produces software implementations. These implementations are time-consuming to develop and some need to be maintained in order to enable building further research upon the implementation. While necessary, these processes can be quickly challenging. This article documents the tools and techniques we have come up with to simplify the maintenance of Mopsa since 2017. Mopsa is a static analysis platform that aims at being sound. First, we describe an automated way to measure precision that does not require any baseline of true bugs obtained by manually inspecting the results. Further, it improves transparency of the analysis, and helps discovering regressions during continuous integration. Second, we have taken inspiration from standard tools observing the concrete execution of a program to design custom tools observing the abstract execution of the analyzed program itself, such as abstract debuggers and profilers. Finally, we report on some cases of automated testcase reduction.
title Easing Maintenance of Academic Static Analyzers
topic Programming Languages
Software Engineering
url https://arxiv.org/abs/2407.12499