Papers for

database system builders

Papers whose findings have a practical use for this group, as judged from the abstract. Open a paper to read what it means in practice.

Mechanizing verification of transactional anomalies in weak isolation levels

Mechanizing Transactional Anomalous Patterns for Weak Isolation Levels

Abstract: Recently proposed transactional anomalous patterns (TAPs) provide a semantic characterization of weak isolation levels and serve as the foundation for TAP-based isolation checking. Yet, these characterizations currently exist only as pen-and-paper proofs. We present the first machine-checked formalization of TAPs and their associated weak isolation levels in Rocq. We further establish machine-checked proofs of the corresponding TAP-based characterization theorems. The mechanization process revealed two subtle issues in the original presentation: an underspecified transaction history model and an incomplete TAP characterization of the Read Atomicity isolation level that failed to capture violations of session guarantees. We address these issues by refining the definition of transaction histories and the corresponding TAP definitions, and re-establish all characterization theorems in Rocq. These refinements have further been integrated into the weak isolation checker Plume.

Tue 6 OctDatabases
The gist
Databases sometimes run several operations at once, which can cause strange behaviors called anomalies. These anomalies happen when the rules that control how operations interact are weak or relaxed. The paper’s authors turned earlier theoretical descriptions of these anomalies into machine-checked proofs, confirming their accuracy and revealing some hidden issues. They fixed these problems and improved the way weak isolation rules are checked, making automated tools more reliable.
Open → 2610.07665v1

Proof shows efficient steps needed to solve extended Datalog programs

Optimal Convergence of Iterative Methods for Datalogo

Abstract: $\mathsf{Datalog}^\circ$ has been introduced as an extension to Datalog that increases expressiveness, yet retains simple least fixpoint semantics and admits optimization techniques such as semi-naïve evaluation and demand transformation. $\mathsf{Datalog}^\circ$ accomplishes this by generalizing the {\em or} and {\em and} operators of Datalog to addition and multiplication over a semiring. Finding a (minimal) fixpoint of a $\mathsf{Datalog}^\circ$ program is equivalent to finding a solution to a system of polynomial equations over the underlying semiring. Solving these systems of polynomial equations is not only a fundamental problem in the theory of $\mathsf{Datalog}^\circ$, but also has many applications in computer science, such as in databases, program analysis, and optimization. This paper resolves a key open problem in the theory of $\mathsf{Datalog}^\circ$: we prove a tight upper bound on the number of steps until convergence of iterative methods for solving these polynomial equation systems over a commutative $p$-stable semiring. In particular, we show that the number of steps until convergence is $O((p+1)n)$ where $n$ is the output size of the $\mathsf{Datalog}^\circ$ program. As the number of steps until convergence is only a proxy for the runtime of $\mathsf{Datalog}^\circ$ evaluation, we also consider the number of semiring operations used and show that, for a natural class of algorithms, $O((p+1)mn)$ is a tight upper bound, where $m$ is the maximum number of semiring operations per iteration.

Fri 2 OctData Structures and Algorithms
The gist
Finding solutions to certain computer problems can be like solving equations with repeated guessing until the answer settles down. The authors studied a version of a programming language called Datalog that is more flexible but still lets you understand how it works mathematically. They proved exactly how many steps it takes for these guessing methods to find the final answers, giving a clear limit that matches what was already known in simpler cases. This helps people know how efficient algorithms based on this language can be.
Open → 2610.04062v1

Improved bounds on weighted matroid intersections and matchoids

Integrality-Gap Bounds for Weighted Matchoids and Matroid Intersection

Abstract: The weighted $k$-matroid intersection problem asks for a maximum-weight set that is independent in each of $k$ matroids on a common ground set. The natural LP relaxation optimizes over the intersection of the $k$ matroid independent set polytopes. It is conjectured that this LP has integrality gap at most $k-1$. The conjecture is known for $k\le3$, but for $k\ge4$ the best general upper bound was $k$. We improve this bound to $k-1+1/k$. More generally, we prove that the natural LP of a $p$-matchoid has integrality gap at most $p-1+1/p$, with a deterministic LP-relative algorithm attaining the same factor. The matchoid extension resolves the $p$-matchoid part of a conjecture of Lee, Sviridenko, and Vondrák; projective planes give explicit tight instances whenever one of order $p-1$ exists.

Fri 18 SeptDiscrete Mathematics
The gist
The paper studies a math problem about picking the best combination of items that satisfy multiple rules at once, called matroids. The authors improved the best known mathematical guarantee for how close a certain relaxation method gets to the true best solution, especially when there are four or more rules. They also extended this to a more general setting called matchoids. Their results get closer to a long-standing prediction and can be matched by a deterministic algorithm.
Open → 2609.21477v1