Data Mining - Concepts and Techniques.

Data Mining Practical Machine Learning Tools and Techniques

This sales letter may not influence you to be smarter, but the book that we offer will evoke you to be smarter. Yeah, at least you'll know more than others who don't. This is what called as the quality life improvisation. Why should this research methods in social relations? It's because this is your favourite theme to read. If you like this theme about, why don't you read the book to enrich your discussion?

Research methods in social relations

Technical foundations introduction software reliability and system reliability the operational profile software reliability modelling survey model evaluation and recalibration techniques practices and experiences best current practice of SRE software reliability measurement experience measurement-based analysis of software reliability software fault and failure classification techniques trend analysis in validation and maintenance software reliability and field data analysis software reliability process assessment emerging techniques software reliability prediction metrics software reliability and testing fault-tolerant SRE software reliability using fault trees software reliability process simulation neural networks and software reliability. Appendices: software reliability tools software failure data set repository.

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Handbook of software reliability engineering

Will Tracz, our esteemed editor and Used-Program salesman, has written an entertaining, non-technical book dealing with the practice (and lack of) of software reuse. Its a collection of essays, mostly rehashed (reused?) and updated from various columns and papers published over the years.. Its a short (a bit over 200 pages) easy reading and enjoyable book (I read most of it in one sitting). Some of the essays discuss what was printed in the past and a discussion of the current status of the points.

Safeware: System Safety and Computers

With the advent of computerization primary goal of organization across the globe was automation of their system, this result in massive collection of data in respective of organization business logic and process, not much was thought about integration of application and data. Once a blessing became huge problem in organizations, data all over the organization was becoming difficult to manage and inconsistency of data resulted in creation of team not meant for development but data management. Many organizations have started reinvesting in data management in the form of creation of Data Warehouse and again organisation across the globe are not stressing upon user needs and demands but only focusing on integration of heterogeneous data sources with goal of making data centralised and consistent by creating Warehouse. 21st century user has needs, he/she not only needs data but needs refined and cleaned data, he/she wants data in his/her desired format. While data integration is paramount need of the hour is to make data stored in such flexible manner so that user can be provided information in his/her desired format. In this paper we introduce methods of data transformation at application level without need to modify underlying structure.

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User desired information translation

Reliability of a software system has been one of the driving forces for the various software engineering processes and methodologies that led to their evolution and sophistication. The concerns for reliability of a software system surface very early on during the development phases of the software system. When it comes to acquisition of reliability, we should not immediately get model-oriented; instead every minutia of software development life cycle should be given its due. This paper outlines the areas where reliability needs to pick up. This paper underlines the fact that it is only through carefully controlled and carefully applied software engineering process that software reliability growth can be achieved. It emphasizes on the acquisition of reliability of software systems as soon as the conception phase. We trace the reliability concerns from the early stage to the fully functional stage. The terms “hard reliability” and “soft reliability” are used.

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On Way to Acquiring Reliability Growth in Software Systems

Reliability attribute of dynamic software systems is a key to the normal operational behavior of such systems. Although the acquisition of perfect(cent percent) level of reliability for software may be practically very difficult but achieving near-perfect reliability growth levels is very much possible using reliability engineering study. Many SRGMs have been proposed including some based on Non-Homogeneous Poisson Process (NHPP). The realistic characteristics about human learning and experiential gains of new skills for better detection and correction of faults on software are being incorporated in such models. This paper incorporates two types of learning effects and a negligence factor into the SRGM with learning effect proposed by Chiu, Huang and Lee, taking advantage of the improvement proposed by Chiu, in terms of introduction of a negligent factor, in Chiu, Huang and Lee SRGM. In this paper, we simultaneously incorporate learning effect that exists in two forms: one is autonomous learning and the other is acquired learning as well as a negligence factor. The resultant model equations are subjected to the statistical analysis and the results are satisfactory.

A software reliability growth model with two types of learning and a negligence factor

Measurement is essential to achieving the basic management objectives of prediction, progress, and process improvement. We cannot build quality software, or improve our process, without measurement. Measurement activities keep us actively involved in, and informed of, product and process. Measurement in testing projects is a challenging, but indispensable element of a software testing process. Software testing today has a multitude of metrics for measuring different aspects of testing. Test metrics are an important indicator of the effectiveness of a software testing process. In this paper we present the various metrics that should be used in software testing. These test metrics may become an important indicator of the effectiveness and efficiency of a software testing process and may also identify risky areas that may need more testing.

S. M. K. Quadri

Papers

User desired information translation

On Way to Acquiring Reliability Growth in Software Systems

A software reliability growth model with two types of learning and a negligence factor

Notable Metrics in Software Testing

Test Cloud before Cloud Test