Software Reliability is an important facet of software quality. Software reliability is the probability of the failure free operation of a computer program for a specified period of time in a specified environment. Software Reliability is dynamic and stochastic. It differs from the hardware reliability in that it reflects design perfection, rather than manufacturing perfection. This article provides an overview of Software Reliability which can be categorized into: modeling, measurement and improvement, and then examines different modeling technique and metrics for software reliability, however, there is no single model that is universal to all the situations. The article will also provide an overview of improving software reliability and then provides various ways to improve software reliability in the life cycle of software development.

The field of a digital-image processing has experienced dramatic growth and increasingly widespread applicability in recent years. Fortunately, advances in computer technology have kept pace with the rapid growth in volume of image data in these and other applications. Digital-image processing has become economical in many fields of research and in industrial and military applications. While each application has requirements unique from the others, all are concerned with faster, cheaper, more accurate, and more extensive computation.Analysis of document images for information extraction has become very prominent in recent past. Wide variety of information, which has been conventionally stored on paper, is now being converted into electronic form for better storage and intelligent processing. This needs processing of documents using image analysis, processing methods. This article provides an overview of various methods used for digital image processing using three main components: Pre-processing, Feature extraction and the Classification. Pre-processing includes Image acquisition, Binarization, identification, Layout analysis, feature extraction and classification. Classification is an important step in Office Automation, Digital Libraries, and other document image analysis applications. This article examines the various methods used for document image processing in order to achieve a processed document having high quality, accuracy and fast retrieval.

Natural Language Processing (NLP) is that field of computer science which consists of interfacing computer representations of information with natural languages used by humans. It examines the use of computers in understanding and manipulating the natural language text and speech. The main aim of the researchers in this field is to collect the necessary details about how natural languages are being used and understood by humans. They use these details to develop the tools for making the computers understand and manipulate the natural languages to perform the desired tasks. In this paper we describe some of the theoretical developments that have influenced research in NLP. We also discuss automatic abstracting and information retrieval in natural language processing applications. We conclude with a discussion on Natural Language Interfaces, NLP software and the future research in NLP. General TermsNatural language processing, Artificial Intelligence.

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