A framework for efficient regression tests on database applications

Regression testing is an important software maintenance activity to ensure the integrity of a software after modification. However, most methods and tools developed for software testing today do not work well for database applications; these tools only work well if applications are stateless or tests can be designed in such a way that they do not alter the state. To execute tests for database applications efficiently, the challenge is to control the state of the database during testing and to order the test runs such that expensive database reset operations that bring the database into the right state need to be executed as seldom as possible. This work devises a regression testing framework for database applications so that test runs can be executed in parallel. The goal is to achieve linear speed-up and/or exploit the available resources as well as possible. This problem is challenging because parallel testing needs to consider both load balancing and controlling the state of the database. Experimental results show that test run execution can achieve linear speed-up by using the proposed framewor

Predicate-based indexing for desktop search

Google and other products have revolutionized the way we search for information. There are, however, still a number of research challenges. One challenge that arises specifically in desktop search is to exploit the structure and semantics of documents, as defined by the application program that generated the data (e.g., Word, Excel, or Outlook). The current generation of search products does not understand these structures and therefore often returns wrong results. This paper shows how today's search technology can be extended in order to take the specific semantics of certain structures into account. The key idea is to extend inverted file index structures with predicates which encode the circumstances under which certain keywords of a document become visible to a user. This paper provides a framework that allows to express the semantics of structures in documents and algorithms to construct enhanced, predicate-based indexes. Furthermore, this paper shows how keyword and phrase queries can be processed efficiently on such enhanced indexes. It is shown that the proposed approach has superior retrieval performance with regard to both recall and precision and has tolerable space and query running time overhead

The Implementation and Performance of Compressed Databases

In this paper, we show how compression can be integrated into a relational database system. Specifically, we describe how the storage manager, the query execution engine, and the query optimizer of a database system can be extended to deal with compressed data. Our main result is that compression can significantly improve the response time of queries if very light-weight compression techniques are used. We will present such light-weight compression techniques and give the results of running the TPC-D benchmark on a so compressed database and a non-compressed database using the AODB database system, an experimental database system that was developed at the Universities of Mannheim and Passau. Our benchmark results demonstrate that compression indeed offers high performance gains (up to 55%) for IO-intensive queries and moderate gains for CPU-intensive queries. Compression can, however, also increase the running time of certain update operations. In all, we recommend to extend today\'s database systems with light-weight compression techniques and to make extensive use of this feature

Benchmarking bitemporal database systems: ready for the future or stuck in the past?

Abstract. Introduction: Many strategic investments are often justified with the argument that they will create synergy. For holding mining establishment the goal was more on how to increase business capacity and funding, management of natural resources of mineral and coal, increase value added through downstream and increase local content, as well as cost efficiency through synergy. This paper aims to find the value of synergy in Inalum, PTBA, ANTM and TINS before establishment holding company of mining and the sensitivity the value to different assumptions and how to improve value of synergy in creating a holding company of mining. The major aims of mining holding company to create value and synergy in mining State-Owned Enterprises, with the expectation, it will increase revenue contribution to the country. These goals could be analyzed and measured by understanding of synergy based on two sources of synergies: operating synergy and financial synergy. This paper will assess operating synergy. Methods: In this valuation, Discounted Cash Flow (DCF) Framework will be used to recognize the potential source of synergy from operation. Results: This study found that gain from operation synergy of increasing growth and cost reduction will maximize the business value amounted USD 3,659,295.63, compared to gain from cost reduction USD -14,181,427.91  and gain from increasing growth USD 644,448.44. Conclusion: Given the results from study, it is important to derive the right strategy from investment decision to reflect the optimal source of synergy in order to maximize the business value in Inalum. Keywords:  DCF, investing decision, maximize business value, value of synerg

A Study of Query Execution Strategies for Client-Server Database Systems

Query processing in a client-server database system raises the question of where to execute queries to minimize the communication costs and response time of a query, and to load-balance the system. This paper evaluates the two common query execution strategies, data shipping and query shipping, and a policy referred to as hybrid shipping. Data shipping determines that queries be executed at clients; query shipping determines that queries be executed at servers; and hybrid shipping provides the flexibility to execute queries at clients and servers. The experiments with a client-server model confirm that the query execution policy is critical for the performance of a system. Neither data nor query shipping are optimal in all situations, and the performance penalities can be substantial. Hybrid shipping at least matches the best performance of data and query shipping and shows better performance than both in many cases. The performance of hybrid shipping plans, however, is shown to be sensitive to changes in the state of the system (e.g., the load of machines and the contents of caches). Initial experiments indicate that an extended version of a 2-step optimization may be an effective strategy for adjusting plans according to the state of the system at runtime. (Also cross-referenced as UMIACS-TR-95-85

Adaptive range filters for cold data: avoiding trips to siberia

ABSTRACT Bloom filters are a great technique to test whether a key is not in a set of keys. This paper presents a novel data structure called ARF. In a nutshell, ARFs are for range queries what Bloom filters are for point queries. That is, an ARF can determine whether a set of keys does not contain any keys that are part of a specific range. This paper describes the principles and methods for efficient implementation of ARFs and presents the results of comprehensive experiments that assess the precision, space, and latency of ARFs. Furthermore, this paper shows how ARFs can be applied to a commercial database system that partitions data into hot and cold regions to optimize queries that involve only hot data