JavaDL: Automatically Incrementalizing Java Bug Pattern Detection
Dura, Alexandru LU
; Reichenbach, Christoph
LU
and Söderberg, Emma
LU
(2021)
ACM SIGPLAN conference on Systems, Programming, Languages, and Applications: Software for Humanity
In Proceedings of the ACM on Programming Languages
5(OOPSLA).
- Abstract
- 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... (More)
- 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. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/c4a4f962-16d5-4494-8d4f-19f87402c13f
- author
- Dura, Alexandru
LU
; Reichenbach, Christoph
LU
and Söderberg, Emma
LU
- organization
- publishing date
- 2021-10-01
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Syntactic Patterns, Software Bugs, Datalog, Static Analysis Frameworks
- in
- Proceedings of the ACM on Programming Languages
- volume
- 5
- issue
- OOPSLA
- article number
- 165
- publisher
- Association for Computing Machinery (ACM)
- conference name
- ACM SIGPLAN conference on Systems, Programming, Languages, and Applications: Software for Humanity
- conference location
- Chicago, United States
- conference dates
- 2021-10-17 - 2021-10-22
- external identifiers
-
- scopus:85117594578
- ISSN
- 2475-1421
- DOI
- 10.1145/3485542
- project
- Performance bug detection through combined static and dynamic program analysis
- language
- English
- LU publication?
- yes
- id
- c4a4f962-16d5-4494-8d4f-19f87402c13f
- date added to LUP
- 2021-10-18 11:39:47
- date last changed
- 2022-05-05 05:00:17
@article{c4a4f962-16d5-4494-8d4f-19f87402c13f,
abstract = {{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.}},
author = {{Dura, Alexandru and Reichenbach, Christoph and Söderberg, Emma}},
issn = {{2475-1421}},
keywords = {{Syntactic Patterns; Software Bugs; Datalog; Static Analysis Frameworks}},
language = {{eng}},
month = {{10}},
number = {{OOPSLA}},
publisher = {{Association for Computing Machinery (ACM)}},
series = {{Proceedings of the ACM on Programming Languages}},
title = {{JavaDL: Automatically Incrementalizing Java Bug Pattern Detection}},
url = {{http://dx.doi.org/10.1145/3485542}},
doi = {{10.1145/3485542}},
volume = {{5}},
year = {{2021}},
}