In the structural Software test, the test data generation is essential. The problem of generating the test data is a search problem, and for solving the problem, the search algorithms can be used. Genetic algorithm is one of the most widely used algorithms in this field. Adjusting the genetic algorithm parameters helps to increase the effectiveness of this algorithm. In this paper, the adaptive genetic algorithm is used in order to maintain the diversity of the population to the test data generation based on the path coverage criterion, which calculates the rate of recombination and mutation with the similarity between the chromosomes and the amount of chromosome fitness during and around each algorithm. The experiments performed show that this method is faster for generating the test data than the other versions of genetic algorithm used by the others.

In this paper, after a review on well-known scenario-based methods of SA evaluation, a different approach is introduced to find architectural defects. The proposed method at first, elicits the problems threatening the system's success. Then based on the analysis of the problems and probable defects which could cause the problems, tests are designed and applied to the system in order to find the real defects specially the architectural ones. Results show that the proposed method could be use to find those architectural defects which may be remained covered after applying the other methods. Therefore, it could be used as a mean to SA Testing and also as a complementary mechanism along with well-known SA evaluation methods. The proposed method and its components are presented in a systematic form. An illustration of its application on the architecture of a real system is presented and the results are compared with the results of applying ATAM on the same architecture.

In the Software development process, Testing is one of the most human intensive steps. Many researchers try to automate test case generation to reduce the manual labor of this step. Negative selection is a famous algorithm in the field of Artificial Immune System (AIS) and many different applications has been developed using its idea. In this paper we have designed a new algorithm based on negative selection for breeding test cases. Our approach, belongs to the category of black-box Software Testing. Moreover, this algorithm can be implemented in a distributed model. Two well-known case studies from Software Testing benchmarks is selected and results show the efficiency of this algorithm.

In the present study, Al-WC (0, 5, 10, 15% weight fractions) nano composite was developed with WC particles as the reinforcement and Al particles as the base metal. The WC (99.5%, 20mm) is mixed (0, 5, 10 & 15% in weight fractions) with Al powder (99.5%, 60μm) and milled separately for 45 h using high energy ball mill (Pulversitte 6, Fritsch-Germany, 50 WC balls, 10mm, b/p 20: 1, 300 rpm). Characterisation (every 9 h) is done using SEM (Hitachi, and SU1510-Japan), Zetasizer (Malvern, Nano ZS90 - UK) and AFM (XE 70, Park Systems - Korea).The particles reach the nano size after 45 h of milling. The raw powders are compacted (200, 250, 300kN), sintered (450oC) and furnace cooled (for 48 h) to prepare the specimens of various aspect ratios (0.3, 0.32, 0.36, 0.38, 0.4, 0.42). The Nano indentation (2nN, AFM, XE 70, Park Systems, Korea), non-destructive (Fallon Ultrasonics, 100MHZ, FUI1050, Canada) and destructive Testing (UTM, 1MN, 5mm/min, 10 kN increments) are carried out on all preforms to evaluate mechanical (axial, hydrostatic, hoop stresses and strains), physical (density, acoustic impedance, hardness) and elastic (Young’s, shear, bulk modulus and Poisson ratio) properties of the composites and then analysed (graphical analysis), and the composite having the best properties (Al-15WC, h/d 0.3, rf 0.79) is identified. Then, its properties are fed into ANSYS Workbench Software (Release14) and FEA analysis (Static structural, 67500 nodes, Linear Solid185 type, 38283 elements) is carried out on the piston (114.7mm3, 1.83 kg), modelled using PRO-E Software. The results show the substantial improvement of the properties of the Al-WC composites compared to the parent metal.

Systems of computers and their application in the lives of modern human beings are vastly expanding. In any kind of computer application, failure in computer systems can lead to a range of financial and mortal losses. Indeed, the major origin of Software failure can be located in designing or implementing Software. With regard to these statistics, 30% of the Software projects have been prosperous and successful. The proposed method is intended to reduce the cost and time of Testing and it focuses on enhancing the efficiency of Software Testing methods. In this paper, we investigated the effect of slicing techniques on the reduction rate of Testing cost and time. The results of experiments show that we can cover a large number of program instructions, branches and paths by a small number of test cases in the sliced program.

Test data generation is one of the costly parts of the Software Testing, which is performed according to the designed test cases. The problem of designing test cases and then generating optimized test data is one of the challenges of the Software Testing, including the mutation Testing technique. mutation Testing has the ability to measure the test cases quality and determine the adequate test cases. However, to perform mutation Testing, you need a test set that provides the maximize Coverage of source code and thus have the ability to identify the program errors. In this work, we use code coverage techniques to design test cases and automatically generate optimized test data using the meta-heuristic FA-MABC algorithm. The results are a test suite that cover and test the maximum number of source code lines. Such test suite is more likely to identify errors and get a higher score in the mutation Testing. In the proposed method to obtain effective test cases, first generated test cases are applied to mutation Testing and then effective test cases are extracted using the Extinguished mutation table. The results of the evaluation show that the FA-MABC algorithm reduces the time of the test data generation, and “modified condition / decision coverage”, increases the mutation score.

The ambient vibration measurement is a kind of output data-only dynamic Testing where the traffics and winds are used as agents responsible for natural or environmental excitation. Therefore an experimental modal analysis procedure for ambient vibration Testing needs to base itself on output-only data. The modal analysis involving output-only measurements present a challenge that requires the use of special modal identification technique, which can deal with very small magnitude of ambient vibration contaminated by noise. Two complementary modal analysis methods are implemented. They are rather simple peak picking (PP) method in frequency domain and more advanced stochastic subspace identification (SSI) method in time domain. According to these methods Graphical User Interface (GUI) Software developed in MATLAB. This program is called SIP and can be used in modal parameter identification of large civil structures such as bridges and towers. This paper presents the application of ambient vibration Testing and experimental modal analysis on large civil engineering structures and also gives brief review of program. Also modal parameters of the Babolsar arch steel bridge are extracted using SIP and ambient vibration data from dynamic test carried out on this bridge.

Test automation is one of the major areas in Software engineering. Test automation can reduce the high cost of Software development and at the same time increases the reliability of the Testing process. In this paper we present a novel specification based framework for automating test process based on use case scenarios. It receives Software specification that defined with UML at design level and source code. One of major byproduct of our framework is test pattern which can be used for other purposes such as design verification.

The increase in complexity and the rate of technological changes in modern Software development have led to a demand for systematic methods that raise the abstraction level for system maintenance and regression Testing. Model Driven Engineering (MDE) has promised to reduce extra coding efforts in Software maintenance activities using traceable change management, especially in rapidly changing application. The paper presents a Z-notation based framework, called Changed-based Regression Testing (ChbRT), for formal modeling of regression Testing in the context of MDE. The framework proposes to automatically propagate the changes from a Software specification to Testing artifacts in order to preserve consistency after system evolution. The framework is enriched by providing a new category of coverage metrics for change-based regression Testing. The proposed framework is expected to be beneficial in both platform independent and specific levels of ChbRT by identifying the suitable coverage according to available Testing resources. The accuracy and efficiency of the proposed framework have been evaluated and analyzed on three case studies.