You are provided with the abstract of a scientific paper and the abstracts of the papers it references. Your task is to write a Related Work section for the main paper. This section should concisely summarize and integrate the key points from the cited abstracts, reflecting how they relate to the main paper's contributions and context. In your summary, use numerical citation markers like [1], [2], etc., to refer to the corresponding papers.

Main Abstract:
CTL is the dominant temporal specification language in practice mainly due to the fact that it admits model checking in linear time. Logic programming and the database query language Datalog are often used as an implementation platform for logic languages. In this paper we present the exact relation between CTL and Datalog and moreover we build on this relation and known efficient algorithms for CTL to obtain efficient algorithms for fragments of stratified Datalog. The contributions of this paper are: a) We embed CTL into STD which is a proper fragment of stratified Datalog. Moreover we show that STD expresses exactly CTL -- we prove that by embedding STD into CTL. Both embeddings are linear. b) CTL can also be embedded to fragments of Datalog without negation. We define a fragment of Datalog with the successor build-in predicate that we call TDS and we embed CTL into TDS in linear time. We build on the above relations to answer open problems of stratified Datalog. We prove that query evaluation is linear and that containment and satisfiability problems are both decidable. The results presented in this paper are the first for fragments of stratified Datalog that are more general than those containing only unary EDBs.

Cited Abstract(s):
[1]: We consider the problems of containment, equivalence, satisfiability and query-reachability for datalog programs with negation. These problems are important for optimizing datalog programs. We show that both query-reachability and satisfiability are decidable for programs with stratified negation provided that negation is applied only to EDB predicates or that all EDB predicates are unary. In the latter case, we show that equivalence is also decidable. The algorithms we present can also be used to push constraints from a given query to the EDB predicates. In showing our decidability results we describe a powerful tool, the query-tree, which is used for several optimization problems for datalog programs. Finally, we show that satisfiability is undecidable for datalog programs with unary IDB predicates, stratified negation and the interpreted predicate ≠.

[2]: Datalog programs, i.e., Prolog programs without function symbols, are considered It is assumed that a variable appearing in the head of a rule must also appear in the body of the rule. The input of a program is a set of ground atoms (which are given in addition to the program's rules) and, therefore, can be viewed as an assignment of relations to some of the program's predicates. Two programs are equivalent if they produce the same result for all possible assignments of relations to the extensional predicates (i.e., the predicates that do not appear as heads of rules). Two programs are uniformly equivalent if they produce the same result for all possible assignments of initial relations to all the predicates (i.e., both extensional and intentional). The equivalence problem for Datalog programs is known to be undecidable. It is shown that uniform equivalence is decidable, and an algorithm is given for minimizing a Datalog program under uniform equivalence. A technique for removing parts of a program that are redundant under equivalence (but not under uniform equivalence) is developed. A procedure for testing uniform equivalence is also developed for the case in which the database satisfies some constraints.

[3]: 

[4]: We study the problem of determining whether a given recursive Datalog program is equivalent to a given nonrecursive Datalog program. Since nonrecursive Datalog programs are equivalent to unions of conjunctive queries, we study also the problem of determining whether a given recursive Datalog program is contained in a union of conjunctive queries. For this problem, we prove doubly exponential upper and lower time bounds. For the equivalence problem, we prove triply exponential upper and lower time bounds.

[5]: Datalog is the language of logic programs without function symbols. It is used as a database query language. If it is possible to eliminate recursion from a Datalog program P, then P is said to be bounded . It is known that the problem of deciding whether a given Datalog program is bounded is undecidable, even for binary programs. We show here that boundedness is decidable for monadic programs, i.e., programs where the recursive predicates are monadic (the non-recursive predicates can have arbitrary arity). Underlying our results are new tools for the optimization of Datalog programs based on automata theory and logic. In particular, one of the tools we develop is a theory of two-way alternating tree automata. We also use our techniques to show that containment for monadic programs is decidable.
Concerning containment of queries the majority of research refers to CQs. However there are important results concerning also Datalog programs. In [1]3 it was pointed out that query containment for monadic Datalog is decidable. The work in [2] shows that checking containment of nonrecursive Datalog queries in Datalog queries is decidable in exponential time. In [4] it is shown that containment of Datalog queries in non-recursive Datalog is decidable in triply exponential time, whereas when the non-recursive query is represented as a union of CQs, the complexity is doubly exponential. In [3] [1] authors proved that equivalence of stratified Datalog programs is decidable but only for programs with unary EDB predicates. Our results are the first that encompass also programs that contain binary EDB predicates.