Consistency guarantees among concurrently executing transactions in local- and distributed systems, commonly referred to as isolation levels, have been formalized in a number of models. Thus far, no model can reason about executable implementations of databases or local transaction libraries providing weak isolation levels. Weak isolation levels are characterized by being highly concurrent and, unlike their stronger counter part serializability, they are not equivalent to the consistency guarantees provided by a transaction library implemented using a global lock. Industrial-strength databases almost exclusively implement weak isolation levels as their default level. This calls for formalism as numerous bugs violating isolation have been detected in these databases. In this paper, we formalize three weak isolation levels in separation logic, namely read uncommitted, read committed, and snapshot isolation. We define modular separation logic specifications that are independent of the underlying transaction library implementation. Historically, isolation levels have been specified using examples of executions between concurrent transactions that are not allowed to occur, and we demonstrate that our specifications correctly prohibit such examples. To show that our specifications are realizable, we formally verify that an executable implementation of a key-value database running the multi-version concurrency control algorithm from the original snapshot isolation paper satisfies our specification of snapshot isolation. Moreover, we prove implications between the specifications—snapshot isolation implies read committed and read committed implies read uncommitted—and thus the verification effort of the database serves as proof that all of our specifications are realizable. All results are mechanized in the Rocq proof assistant on top of the Iris separation logic framework.

Pointer analysis is one of the fundamental problems in static program analysis. Given a set of pointers, the task is to produce a useful over-approximation of the memory locations that each pointer may point-to at runtime. The most common formulation is Andersen’s Pointer Analysis (APA), defined as an inclusion-based set of m pointer constraints over a set of n pointers. Scalability is extremely important, as points-to information is a prerequisite to many other components in the static-analysis pipeline. Existing algorithms solve APA in O ( n 2 · m ) time, while it has been conjectured that the problem has no truly sub-cubic algorithm, with a proof so far having remained elusive. It is also well-known that APA can be solved in O ( n 2 ) time under certain sparsity conditions that hold naturally in some settings. Besides these simple bounds, the complexity of the problem has remained poorly understood. In this work we draw a rich fine-grained and parallel complexity landscape of APA, and present upper and lower bounds. First, we establish an O ( n 3 ) upper-bound for general APA, improving over O ( n 2 · m ) as n = O ( m ). Second, we show that even on-demand APA (“may a specific pointer a point to a specific location b ?”) has an Ω( n 3 ) (combinatorial) lower bound under standard complexity-theoretic hypotheses. This formally establishes the long-conjectured “cubic bottleneck” of APA, and shows that our O ( n 3 )-time algorithm is optimal. Third, we show that under mild restrictions, APA is solvable in Õ( n ω ) time, where ω<2.373 is the matrix-multiplication exponent. It is believed that ω=2+ o (1), in which case this bound becomes quadratic. Fourth, we show that even under such restrictions, even the on-demand problem has an Ω( n 2 ) lower bound under standard complexity-theoretic hypotheses, and hence our algorithm is optimal when ω=2+ o (1). Fifth, we study the parallelizability of APA and establish lower and upper bounds: (i) in general, the problem is P-complete and hence unlikely parallelizable, whereas (ii) under mild restrictions, the problem is parallelizable. Our theoretical treatment formalizes several insights that can lead to practical improvements in the future.