JavaDL: Automatically Incrementalizing Java Bug Pattern Detection

Forskningsoutput: TidskriftsbidragArtikel i vetenskaplig tidskriftPeer review

Sammanfattning

Static checker frameworks support software developers by automatically discovering bugs that fit general-purpose bug patterns. These frameworks ship with hundreds of detectors for such patterns and allow developers to add custom detectors for their own projects. However, existing frameworks generally encode detectors in imperative specifications, with extensive details of not only what to detect but also how. These details complicate detector maintenance and evolution, and also interfere with the framework’s ability to change how detection is done, for instance, to make the detectors incremental. In this paper, we present JavaDL, a Datalog-based declarative specification language for bug pattern detection in Java code. JavaDL seamlessly supports both exhaustive and incremental evaluation from the same detector specification. This specification allows developers to describe local detector components via syntactic pattern matching, and nonlocal (e.g., interprocedural) reasoning via Datalog-style logical rules. We compare our approach against the well-established SpotBugs and Error Prone tools by re-implementing several of their detectors in JavaDL. We find that our implementations are substantially smaller and similarly effective at detecting bugs on the Defects4J benchmark suite, and run with competitive runtime performance. In our experiments, neither incremental nor exhaustive analysis can consistently outperform the other, which highlights the value of our ability to transparently switch execution modes. We argue that our approach showcases the potential of clear-box static checker frameworks that constrain the bug detector specification language to enable the framework to adapt and enhance the detectors.
Originalspråkengelska
Artikelnummer165
TidskriftProceedings of the ACM on Programming Languages
Volym5
NummerOOPSLA
DOI
StatusPublished - 2021 okt. 1
EvenemangACM SIGPLAN conference on Systems, Programming, Languages, and Applications: Software for Humanity - Virtual + In-Person, Chicago, USA
Varaktighet: 2021 okt. 172021 okt. 22
https://2021.splashcon.org/

Ämnesklassifikation (UKÄ)

  • Programvaruteknik

Fingeravtryck

Utforska forskningsämnen för ”JavaDL: Automatically Incrementalizing Java Bug Pattern Detection”. Tillsammans bildar de ett unikt fingeravtryck.
  • MetaDL: Declarative program analysis for the masses

    Dura, A. & Balldin, H., 2019 okt. 20, SPLASH Companion 2019 - Proceedings Companion of the 2019 ACM SIGPLAN International Conference on Systems, Programming, Languages, and Applications: Software for Humanity. Smaragdakis, Y. (red.). Association for Computing Machinery (ACM), s. 17-18 2 s. (SPLASH Companion 2019 - Proceedings Companion of the 2019 ACM SIGPLAN International Conference on Systems, Programming, Languages, and Applications: Software for Humanity).

    Forskningsoutput: Kapitel i bok/rapport/Conference proceedingKonferenspaper i proceedingPeer review

Citera det här