Compact Difference Bound Matrices

The Octagon domain, which tracks a restricted class of two variable inequality, is the abstract domain of choice for many applications because its domain operations are either quadratic or cubic in the number of program variables. Octagon constraints are classically represented using a Difference Bound Matrix (DBM), where the entries in the DBM store bounds c for inequalities of the form x_i - x_j <= c, x_i + x_j <= c or -x_i - x_j <= c. The size of such a DBM is quadratic in the number of variables, giving a representation which can be excessively large for number systems such as rationals. This paper proposes a compact representation for DBMs, in which repeated numbers are factored out of the DBM. The paper explains how the entries of a DBM are distributed, and how this distribution can be exploited to save space and significantly speed-up long-running analyses. Moreover, unlike sparse representations, the domain operations retain their conceptually simplicity and ease of implementation whilst reducing memory usage

Closing the Performance Gap between Doubles and Rationals for Octagons

Octagons have enduring appeal because their domain opera- tions are simple, readily mapping to for-loops which apply max, min and sum to the entries of a Difference Bound Matrix (DBM). In the quest for efficiency, arithmetic is often realised with double-precision floating- point, albeit at the cost of the certainty provided by arbitrary-precision rationals. In this paper we show how Compact DBMs (CoDBMs), which have recently been proposed as a memory refinement for DBMs, enable arithmetic calculation to be short-circuited in various domain operations. We also show how comparisons can be avoided by changing the tables which underpin CoDBMs. From the perspective of implementation, the optimisations are attractive because they too are conceptually simple, following the ethos of Octagons. Yet they can halve the running time on rationals, putting CoDBMs on rationals on a par with DBMs on doubles

Incrementally Closing Octagons

The octagon abstract domain is a widely used numeric abstract domain expressing relational information between variables whilst being both computationally efficient and simple to implement. Each element of the domain is a system of constraints where each constraint takes the restricted form ±xi±xj≤c. A key family of operations for the octagon domain are closure algorithms, which check satisfiability and provide a normal form for octagonal constraint systems. We present new quadratic incremental algorithms for closure, strong closure and integer closure and proofs of their correctness. We highlight the benefits and measure the performance of these new algorithms