In 2007, Michael Stonebraker and his colleagues published several papers that strongly stated a necessity of radical rethink of DBMSs’ architectures. These suggestions were supported by experiments with some new architectures targeted to applications of data streams, data analysis, online transaction processing, etc. In 2008, the Clermont Report on research directions in the field of database technology acknowledged these trends. The most interesting publication of 2009 briefly discussed in this paper show that researchers and developers of database management facilities seriously perceived the idea of rethinking of DBMSs’ architectures.

The approaches of use of MapReduce technology together with analytical DBMSs are discussed. The paper considers approaches where one implements MapReduce within a kernel of a parallel DBMS, where MapReduce serves as a communication infrastructure of a new parallel DBMS, and where one uses MapReduce in a symbiotic unity with a parallel DBMS. As examples of the first approach, we consider features of massively-parallel DBMSs Greenplum Database and nCluster of Greenplum and Aster Data Systems companies correspondingly. The second approach is used in the project HadoopDB of the universities Yale and Brown. Finally, the third approach the Vertica company is developing.

Data exchange is a way to increase possibilities of local decision support systems on the base of other users experience. Two methods of access to the data distributed in the network are discussed: one is virtual integration (using data without real migration) while the other is knowledge consolidation (data import).

The problem described concerns with multi-parametric control of a very complicated object as a process with complex interference of actions. For such objects it is hard or even impossible to obtain an adequate behavioral model. The approach to the “control process” formalization is developed. This approach is based on the theory of adaptive control, problem solving, data mining and case-based reasoning. The goal of programming system design is to provide a facility for adequate control under conditions of numerous external actions with complex non-parameterized interference.

Object-oriented constraint-based programming (OOCP) combines two orthogonal, but complementary programming paradigms, namely: object-oriented programming (OOP) and constraint logic programming (CLP). In spite of the idea to synthesize these paradigms looks very attractive and there were known attempts to implement it, there is still not clear which constructive form it can achieve during further elaboration and development. The key issues are expressiveness of the applied constraint problem description and its algorithmic solvability. In this paper a new system approach to implementation OOCP based on usage of declarative data modeling languages is proposed and discussed.

The issues of efficiency and robustness of local propagation methods in conformity to constraint-based programming applications are discussed. Comparative analysis of known algorithms is given and new combined method is proposed. The method allows solving of wider classes of constraint problems for polynomial time. The results of computational experiments are presented to illustrate the method advantages over traditional algorithms.

In this paper NP complete strip packing problem is analyzed. New heuristic algorithm on the base of modified Nelder–Mead method, genetic and linear programming algorithms for strip packing problem was proposed. Experiments on the well known tests show that this algorithm has certain advantages. Prospects for convex polygons packing were proposed. Possibility for parallel performance of the algorithm is shown.

In the article an on-line algorithm for packing rectangles into a strip is presented and studied. The estimation of expected wasted ratio for the algorithm is obtained.

This paper offers a model which allows describe operational semantics of machine instructions for various target architectures. Feature of this model is that it is intended for reverse transformation compared with classical compilation one, however the model allows efficiently perform various optimizations. The target architectures are described by external specifications. We present a prototype subsystem for interpretation of the described model.

The article is devoted to solving the problem of reducing the power consumption during the code execution. The object of research is a technique of disabling individual components of the central processing unit. The theoretical aspects of source code modifications are considered in the article for increasing power saving effect of disabling the processor components.

One of widespread applications in binary code analysis is format recovery for files and network messages. If studied code is protected from analysis, analytic suffers from unacceptable time-intense expenses. In this paper we propose a method for automated format recovery. The method is based on binary code dynamic analysis and allows recovering hierarchical structure of analyzed memory buffers, and, moreover, recover semantics for certain fields. We present prototype tool, which supports the described method, and evaluate the tool using a model sample.