Fundamentals and applications of order dependencies

Business-intelligence queries often involve SQL functions and algebraic expressions. There can be clear semantic relationships between a column's values and the values of a function over that column. A common property is monotonicity: as the column's values ascend, so do the function's values (or the other column's values). This we call an order dependency (OD). Queries can be evaluated more efficiently when the query optimizer uses order dependencies. They can be run even faster when the optimizer can also reason over known ODs to infer new ones. Order dependencies can be declared as integrity constraints, and they can be detected automatically for many types of SQL functions and algebraic expressions. We present optimization techniques using ODs for queries that involve join, order by, group by, partition by, and distinct. Essentially, ODs can further exploit interesting orders to eliminate or simplify potentially expensive sorts in the query plan. We evaluate these techniques over our prototype implementation in IBM® DB2® using the TPC-DS® benchmark schema and some customer inspired queries. Our experimental results demonstrate a significant performance gain. Dependencies have played an important role in database theory. We study the theoretical aspects of order dependencies-and unidirectional order dependencies (UODs), a proper sub-class of ODs-which describe the relationships among lexicographical orderings of sets of tuples. We investigate the inference problem for order dependencies. We establish the following: (i) a sound and complete axiomatization for UODs which is sound for ODs; (ii) a hierarchy of order dependency classes; (iii) a proof of co-NP-completeness of the inference problem for ODs and for the subclass of UODs; (iv) a proof of co-NP-completeness of the inference problem of functional dependencies (FDs) from ODs in general, but demonstrate linear time complexity for the inference of FDs from UODs; (v) a sound and complete elimination procedure for testing logical implication over ODs; and (vi) a sound and complete polynomial inference algorithm for sets of UODs over natural domains

Interval-based temporal functional dependencies: specification and verification

In the temporal database literature, every fact stored in a database may beequipped with two temporal dimensions: the valid time, which describes the time whenthe fact is true in the modeled reality, and the transaction time, which describes the timewhen the fact is current in the database and can be retrieved. Temporal functional dependencies(TFDs) add valid time to classical functional dependencies (FDs) in order to expressdatabase integrity constraints over the flow of time. Currently, proposals dealing with TFDsadopt a point-based approach, where tuples hold at specific time points, to express integrityconstraints such as \u201cfor each month, the salary of an employee depends only on his role\u201d. Tothe best of our knowledge, there are no proposals dealing with interval-based temporal functionaldependencies (ITFDs), where the associated valid time is represented by an intervaland there is the need of representing both point-based and interval-based data dependencies.In this paper, we propose ITFDs based on Allen\u2019s interval relations and discuss theirexpressive power with respect to other TFDs proposed in the literature: ITFDs allow us toexpress interval-based data dependencies, which cannot be expressed through the existingpoint-based TFDs. ITFDs allow one to express constraints such as \u201cemployees starting towork the same day with the same role get the same salary\u201d or \u201cemployees with a given roleworking on a project cannot start to work with the same role on another project that willend before the first one\u201d. Furthermore, we propose new algorithms based on B-trees to efficientlyverify the satisfaction of ITFDs in a temporal database. These algorithms guaranteethat, starting from a relation satisfying a set of ITFDs, the updated relation still satisfies thegiven ITFDs

Model Synchronization for Software Evolution

Software evolution refers to continuous change that a software system endures from inception to retirement. Each change must be efficiently and tractably propagated across models representing the system at different levels of abstraction. Model synchronization activities needed to support the systematic specification and analysis of evolution activities are still not adequately identified and formally defined. In our research, we first introduce a formal notation for the representation of domain models and model instances to form the theoretical basis for the proposed model synchronization framework. Besides conforming to a generic MOF metamodel, we consider that each software model also relates to an application domain context (e.g., operating systems, web services). Therefore, we are addressing the problems of model synchronization by focusing on domain-specific contexts. Secondly, we identify and formally define model dependencies that are needed to trace and propagate changes across system models at different levels of abstraction, such as from design to source code. The approach for extraction of these dependencies is based on Formal Concept Analysis (FCA) algorithms. We further model identified dependencies using Unified Modeling Language (UML) profiles and constraints, and utilize the extracted dependency relations in the context of coarse-grained model synchronization. Thirdly, we introduce modeling semantics that allow for more complex profile-based dependencies using Triple Graph Grammar (TGG) rules with corresponding Object Constraint Language (OCL) constraints. The TGG semantics provide for fine-grained model synchronization, and enable compliance with the Query/View/Transformation (QVT) standards. The introduced framework is assessed on a large, industrial case study of the IBM Commerce system. The dependency extraction framework is applied to repositories of business process models and related source code. The extracted dependencies were evaluated by IBM developers, and the corresponding precision and recall values calculated with results that match the scope and goals of the research. The grammar-based model synchronization and dependency modelling using profiles has also been applied to the IBM Commerce system, and evaluated by the developers and architects involved in development of the system. The results of this experiment have been found to be valuable by stakeholders, and a patent codifying the results has been filed by the IBM organization and has been granted. Finally, the results of this experiment have been formalized as TGG rules, and used in the context of fine-grained model synchronization

Optimized Memory Access For Dynamically Scheduled High Level Synthesis

Dynamically-scheduled elastic circuits generated by High-Level Synthesis (HLS) tools are inherently out-of-order, following the flow of data rather than the evolution of an instruction pointer. Components of the circuit which access memory need to be connected to a Load-Store Queue (LSQ) that dynamically checks for memory dependencies, performs store ordering and forwarding, and allows unordered access to Random-Access Memory (RAM) whenever possible. While connecting every memory access (load/store) component to an LSQ ensures correctness of program execution, the hardware and power cost makes this solution unattractive. Statically ruling out dependencies allows circuits to access memory via lightweight components that use an arbitrator to handle RAM port sharing. Reducing the number of components using the LSQ allows the compiler to generate smaller queues which results in superlinear savings in hardware and power for the memory subsystem. This work describes additions to the Elastic Compiler (EC) that allow it to analyze algorithms expressed in LLVM-IR, an intermediate code representation, to rule out memory dependencies between load/store instructions and their underlying insights. These analyses leverage pointer analysis as well as array access patterns to narrow down the list of possibly dependent instructions. We also enhance the compiler to leverage our analyses and automatically generate relevant memory-access components for the circuit and to connect them to the relevant arbitrator or LSQ