OBDDs
E824078
binary decision diagram
canonical representation of Boolean functions
graph-based data structure
reduced ordered binary decision diagram
symbolic representation
OBDDs (Ordered Binary Decision Diagrams) are a canonical, graph-based representation of Boolean functions that enables efficient manipulation and verification in formal methods and model checking.
All labels observed (1)
| Label | Occurrences |
|---|---|
| OBDDs canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T9838515 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: OBDDs Context triple: [Symbolic Model Checking, usesDataStructure, OBDDs]
-
A.
Davis–Putnam algorithm
The Davis–Putnam algorithm is a pioneering procedure in automated theorem proving and propositional logic satisfiability that laid foundational groundwork for modern SAT solvers.
-
B.
Satisfiability Modulo Theories (SMT)
Satisfiability Modulo Theories (SMT) is a framework in computer science and mathematical logic for deciding the satisfiability of logical formulas with respect to background theories such as arithmetic, bit-vectors, arrays, and data types, widely used in verification, synthesis, and automated reasoning.
-
C.
CDCL SAT solver
A CDCL SAT solver is an advanced algorithm for solving Boolean satisfiability problems that extends the classic DPLL approach with conflict-driven clause learning and non-chronological backtracking to greatly improve efficiency on large, complex instances.
-
D.
OBDA systems
OBDA systems are software frameworks that enable querying heterogeneous data sources through an ontology-based abstraction layer, typically using languages like OWL 2 QL to provide semantic integration and efficient query answering.
-
E.
Edge-Based Clausal Syntax
Edge-Based Clausal Syntax is a theoretical linguistics work by Paul Postal that develops a clause structure framework organized around hierarchical edge positions rather than traditional phrase-structure configurations.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: OBDDs Target entity description: OBDDs (Ordered Binary Decision Diagrams) are a canonical, graph-based representation of Boolean functions that enables efficient manipulation and verification in formal methods and model checking.
-
A.
Davis–Putnam algorithm
The Davis–Putnam algorithm is a pioneering procedure in automated theorem proving and propositional logic satisfiability that laid foundational groundwork for modern SAT solvers.
-
B.
Satisfiability Modulo Theories (SMT)
Satisfiability Modulo Theories (SMT) is a framework in computer science and mathematical logic for deciding the satisfiability of logical formulas with respect to background theories such as arithmetic, bit-vectors, arrays, and data types, widely used in verification, synthesis, and automated reasoning.
-
C.
CDCL SAT solver
A CDCL SAT solver is an advanced algorithm for solving Boolean satisfiability problems that extends the classic DPLL approach with conflict-driven clause learning and non-chronological backtracking to greatly improve efficiency on large, complex instances.
-
D.
OBDA systems
OBDA systems are software frameworks that enable querying heterogeneous data sources through an ontology-based abstraction layer, typically using languages like OWL 2 QL to provide semantic integration and efficient query answering.
-
E.
Edge-Based Clausal Syntax
Edge-Based Clausal Syntax is a theoretical linguistics work by Paul Postal that develops a clause structure framework organized around hierarchical edge positions rather than traditional phrase-structure configurations.
- F. None of above. chosen
Statements (52)
| Predicate | Object |
|---|---|
| instanceOf |
binary decision diagram
ⓘ
canonical representation of Boolean functions ⓘ graph-based data structure ⓘ reduced ordered binary decision diagram ⓘ symbolic representation ⓘ |
| abbreviation | OBDD NERFINISHED ⓘ |
| canonicalUnderCondition |
fixed variable ordering
ⓘ
reduction rules applied ⓘ |
| constraint | variables follow a total order along all paths ⓘ |
| definedBy | Bryant 1986 paper on graph-based algorithms for Boolean function manipulation ⓘ |
| edgeType |
high (true) edge
ⓘ
low (false) edge ⓘ |
| fullName | Ordered Binary Decision Diagram NERFINISHED ⓘ |
| generalizationOf | binary decision tree ⓘ |
| hasComponent |
decision nodes
ⓘ
directed edges ⓘ root node ⓘ terminal nodes ⓘ |
| hasProperty |
can be exponentially larger than other representations for some functions
ⓘ
can be exponentially more compact than truth tables for some functions ⓘ each variable is tested at most once along any path ⓘ no isomorphic subgraphs ⓘ no redundant tests ⓘ reduced form is canonical for a fixed variable ordering ⓘ size strongly depends on variable ordering ⓘ supports efficient equivalence checking of Boolean functions ⓘ supports efficient logical operations ⓘ supports efficient model counting for Boolean functions ⓘ supports efficient quantification over variables ⓘ supports efficient restriction of variables ⓘ supports efficient satisfiability checking ⓘ variables are tested in a fixed order ⓘ |
| hasVariant | ROBDD NERFINISHED ⓘ |
| implementedIn |
BuDDy library
NERFINISHED
ⓘ
CUDD library NERFINISHED ⓘ JavaBDD library NERFINISHED ⓘ |
| introducedBy | Randal E. Bryant NERFINISHED ⓘ |
| represents | Boolean function ⓘ |
| terminalNodeValues |
0
ⓘ
1 ⓘ |
| usedIn |
combinational circuit verification
ⓘ
equivalence checking of circuits ⓘ formal verification ⓘ hardware verification ⓘ logic synthesis ⓘ model checking ⓘ probabilistic model analysis ⓘ software verification ⓘ symbolic model checking ⓘ test pattern generation ⓘ timing analysis ⓘ |
| yearIntroduced | 1986 ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: OBDDs Description of subject: OBDDs (Ordered Binary Decision Diagrams) are a canonical, graph-based representation of Boolean functions that enables efficient manipulation and verification in formal methods and model checking.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.