Software Testing and Documenting Automation

This article describes some approaches to problem of testing and documenting automation in information systems with graphical user interface. Combination of data mining methods and theory of finite state machines is used for testing automation. Automated creation of software documentation is based on using metadata in documented system. Metadata is built on graph model. Described approaches improve performance and quality of testing and documenting processes.

On Statistical Hypothesis Testing via Simulation Method

A procedure for calculating critical level and power of likelihood ratio test, based on a Monte-Carlo simulation method is proposed. General principles of software building for its realization are given. Some examples of its application are shown.

A Log Tool for Software Systems Analyses

The article presents a new type of logs merging tool for multiple blade telecommunication systems based on the development of a new approach. The introduction of the new logs merging tool (the Log Merger) can help engineers to build a processes behavior timeline with a flexible system of information structuring used to assess the changes in the analyzed system. This logs merging system based on the experts experience and their analytical skills generates a knowledge base which could be advantageous in further decision-making expert system development. This paper proposes and discusses the design and implementation of the Log Merger, its architecture, multi-board analysis of capability and application areas. The paper also presents possible ways of further tool improvement e.g. - to extend its functionality and cover additional system platforms. The possibility to add an analysis module for further expert system development is also considered.

Performance Comparison of MATLAB and Neuro Solution Software on Estimation of Fuel Economy by Using Artificial Neural Network

In the world, scientific studies increase day by day and computer programs facilitate the human’s life. Scientists examine the human’s brain’s neural structure and they try to be model in the computer and they give the name of artificial neural network. For this reason, they think to develop more complex problem’s solution. The purpose of this study is to estimate fuel economy of an automobile engine by using artificial neural network (ANN) algorithm. Engine characteristics were simulated by using “Neuro Solution” software. The same data is used in MATLAB to compare the performance of MATLAB is such a problem and show its validity. The cylinder, displacement, power, weight, acceleration and vehicle production year are used as input data and miles per gallon (MPG) are used as target data. An Artificial Neural Network model was developed and 70% of data were used as training data, 15% of data were used as testing data and 15% of data is used as validation data. In creating our model, proper neuron number is carefully selected to increase the speed of the network. Since the problem has a nonlinear structure, multi layer are used in our model.

A Framework for Design-Time Testing of Service-Based Applications at BPEL Level

Software applications created on top of the service-oriented architecture (SOA) are increasingly popular but testing them remains a challenge. In this paper a framework named TASSA for testing the functional and non-functional behaviour of service-based applications is presented. The paper focuses on the concept of design time testing, the corresponding testing approach and architectural integration of the consisting TASSA tools. The individual TASSA tools with sample validation scenarios were already presented with a general view of their relation. This paper’s contribution is the structured testing approach, based on the integral use of the tools and their architectural integration. The framework is based on SOA principles and is composable depending on user requirements.

Generation of Testing Source Code for Object-Oriented Programs

Красимир Манев, Антон Желязков, Станимир Бойчев - В статията е представена имплементацията на последната фаза на автоматичен генератор на тестови данни за структурно тестване на софтуер, написан на обектно-ориентиран език за програмиране – генерирането на изходен код на тестващия модул. Някои детайли от имплементацията на останалите фази, които са важни за имплементацията на последната фаза, са представени първо. След това е описан и алгоритъмът за генериране на кода на тестващия модул.