Demo Data from EDBT 2026 / reviewers in the wild / expert
Justin Pham
dblp:362/2331
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2023
0009-0005-3064-0601ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 1 · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Software engineering, system software, and programming languages
1 paper |
Programming languages and type systems · 67% Program analysis · 33% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Programming languages and type systems › type checking
pluggable type checking |
0.7 | 1 | 2023 | Practical Inference of Nullability Types · ESEC/SIGSOFT FSE 2023 |
Program analysis
static analysis |
0.7 | 1 | 2023 | Practical Inference of Nullability Types · ESEC/SIGSOFT FSE 2023 |
Programming languages and type systems
type inference |
0.7 | 1 | 2023 | Practical Inference of Nullability Types · ESEC/SIGSOFT FSE 2023 |
Methods — techniques the papers use, named apart from their topics
type qualifier inference · 0.7black-box oracle search · 0.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | Practical Inference of Nullability TypesabstractNullPointerExceptions (NPEs), caused by dereferencing null, fre- quently cause crashes in Java programs. Pluggable type checking is highly effective in preventing Java NPEs. However, this approach is difficult to adopt for large, existing code bases, as it requires manually inserting a significant number of type qualifiers into the code. Hence, a tool to automatically infer these qualifiers could make adoption of type-based NPE prevention significantly easier. We present a novel and practical approach to automatic inference of nullability type qualifiers for Java. Our technique searches for a set of qualifiers that maximizes the amount of code that can be successfully type checked. The search uses the type checker as a black box oracle, easing compatibility with existing tools. However, this approach can be costly, as evaluating the impact of a qualifier requires re-running the checker. We present a technique for safely evaluating many qualifiers in a single checker run, dramatically reducing running times. We also describe extensions to make the approach practical in a real-world deployment. We implemented our approach in an open-source tool Null- AwayAnnotator, designed to work with the NullAway type checker. We evaluated NullAwayAnnotator’s effectiveness on both open- source projects and commercial code. NullAwayAnnotator re- duces the number of reported NullAway errors by 69.5% on average. Further, our optimizations enable NullAwayAnnotator to scale to large Java programs. NullAwayAnnotator has been highly effective in practice: in a production deployment, it has already been used to add NullAway checking to 160 production modules totaling over 1.3 million lines of Java code. Nima Karimipour, Justin Pham, Lazaro Clapp, Manu Sridharan |
ESEC/SIGSOFT FSE | 2 |