Bringing Common Subexpression Problem from the Dark to Light: Towards Large-Scale Workload Optimizations

Streamlining Temporal Formal Verification over Columnar Databases

“…In spite of the ActivityTable also appearing in SQLMiner's log representation [17] (except for the Prev and Next columns), this still used an off-the-shelf relational database engine and a translation of Declare specification into SQL for carrying out formal verification tasks over a dataless log. KnoBAB showed a new pathway for enhancing temporal queries over customary main memory relational database through the combined provision of both ad hoc relational operators expressing LTL f over relational tables (xtLTL f ) and the definition of a query plan represented as a rooted DAG where shared subqueries are computed only once [29]. This was sensibly different from competing approaches [40,41] also relying on main memory engines where, instead, the query plan associated to a formal verification task is always expressed in terms of trees, thus not allowing the detection of shared sub-expressions to be merged to avoid wasteful recomputations.…”

“…In the context of formal specification tasks expressed in LTL f , recent research clearly remarked on the inadequacy of off-the-shelf row-based relational databases and SQL as a query language for expressing LTL f temporal constraints, as it clearly showed that a customized relational algebra for expressing formal specification (eXTended LTL f , xtLTL f [28]) and query plan minimizing the running of sub-queries [29] running on customized columnbased storage (KnoBAB [28,30]) outperformed the previous solution. The main benefit of this approach is that any LTL f can be directly expressed in terms of xtLTL f , while highlevel and human-readable temporal constraints expressed through temporal clauses can be directly specified in a semantics query at warm-up, thus allowing the support of any declarative temporal language (queryplan in Figure 1).…”