Mukesh Kumar Rohil

Using Genetic Algorithm for Unit Testing of Object Oriented Software

Genetic algorithms have been successfully applied in the area of software testing. The demand for automation of test case generation in object oriented software testing is increasing. Genetic algorithms are well applied in procedural software testing but a little has been done in testing of object oriented software. In this paper, we propose a method to generate test cases for classes in object oriented software using a genetic programming approach. This method uses tree representation of statements in test cases. Strategies for encoding the test cases and using the objective function to evolve them as suitable test case are proposed.

An experimental measurement of contradictory judgement matrices in AHP

Often Multi Criteria Decision Making (MCDM) techniques are used to assist in deciding a best choice, or alternative, in many different types of environment. Analytic Hierarchy Process (AHP) is one of the most popular MCDM technique used in variety of domains. It not only generates numerical order of alternatives that indicates an order of preference among them but also reflect there intensity or cardinal preference among them. Despite its advantages and popularity, AHP is often criticized in the literature for many reasons. One such reason is the Consistency Index which it requires to compute for every judgement matrix. As a result of this, it allows the consideration of Contradictory matrices for which no true ordinal ranking satisfying all the relations contained in the judgement matrix can exist. This paper shows the results of an experimental analysis as an attempt to measure the magnitude of this problem. Results show that as the order of pair wise comparison matricx increases the intensity of this problem also increases.

Mobile Data Offloading: Benefits, Issues, and Technological Solutions

Apart from voice services, data made its foray in cellular networks with 2.5G networks. Today, with 3G network already in place, the data requirements of mobile subscribers is very high. With the increasing demand for mobile internet and rich data services such as streaming media for audio and video, this data requirement is expected to multifold in near future. Correspondingly the existing network infrastructures will have to scale to satisfy this huge bandwidth demand in future. The simple solution for this is to build up new infrastructure. But huge investments are involved with it. So, network operators have started looking for the alternative ways of satisfying this data needs. Among many alternatives, mobile data offloading is a most promising one. This paper presents the extensive need, benefits, and technological solutions for Mobile data offloading.

Image feature detection using an improved implementation of maximally stable extremal regions for augmented reality applications

ABSTRACT Augmented Reality for all practical purposes requires extensive computation, accurate view alignment and real-time performance. To address some of these limitations, an improved method of feature detection is proposed using Maximally Stable Extremal Regions. The approach used for feature detection extracts the regions of interest using a true flood fill approach for building and maintaining the component tree. This approach has true worst-case linear complexity (Linear-MSER). In the present work, Linear-MSER is implemented at multiple scales of an image in order to increase the affine invariance properties of the detector (MSLinear-MSER). The two detectors, Linear-MSER and MSLinear-MSER, are then combined separately with Scale Invariant Feature Transform and Speeded-Up Robust Feature descriptors for performance comparison. Performance evaluation is done under varying imaging conditions like changes in viewpoint, scale, blur, illumination and JPEG compression. Results show that, MSLinear-MSER+SIFT performs best in terms of time-complexity and number of keypoint matches when executed at six octaves and five levels. This observation is true for all image-sets taken into consideration, containing images that are affine transformed in one way or other. To exhibit the efficiency of MSLinear-MSER+SIFT, a prototype of an AR system is also developed and discussed in this article using this approach.

Exploring possible applications of augmented reality in education

In recent years, use of Augmented Reality (AR) has been explored in a wide range of applications in various fields. Among these, one of the most inquired is the field of education. Many of these studies have shown that the use of AR in any learning environment promotes critical thinking, better understanding and motivates the learner for further studies. This is due to the real-time experience that AR brings with it to the learners. This paper reports some of the recent studies that list positive and negative impact of AR in an educational setting and how beneficial the employment of this technology is. The paper also gives an overview of some of the possible and promising applications of AR in the fields of science, social science, mathematics and language. Furthermore, the paper discusses trends and the vision towards future opportunities for possible research in augmented reality for education.

An Experimental Study of Markerless Image Registration Methods on Varying Quality of Images for Augmented Reality Applications

Robustness of Augmented Reality (AR) applications depends heavily on image registration procedures. The registration process in AR either make use of manually placed markers in the scene or use natural features extracted from the scene. These markers or detected features estimate the correct position of virtual objects that are to be integrated with the view of real environment. Use of markers for this purpose have only limited applicability. Therefore, for incorporating AR in a wide variety of applications, there is a need for detecting affine invariant and stable natural features from an image. This paper presents a comparative study of six feature detectors, which could be used for the 3D registration process in AR. These feature detectors are applied on 48 images (eight image-sets with six images in each set) varying in terms of change of viewpoint, scale, blur, illumination and compression ratio. Detectors chosen for comparison are Harris-Affine, Hessian-Affine, MSER, SIFT, ASIFT and SURF. The novelty of the work done is the usage of image quality metrics and Pearson Coefficient to study the traits of number of detected keypoints in an image and number of matches between two images with respect to image quality. RANSAC algorithm is used for determining correct number of correspondences between two images by eliminating outliers. Experimental results show that in most cases, performance of feature detectors could be correlated with the quality of images used for experimentation. The comparative evaluation of feature detectors is also done with respect to computational complexity to reason detectors applicability or inapplicability in an AR system.

Exploring Possibilities of Reducing Maintenance Effort in Object Oriented Software by Minimizing Indirect Coupling

The quality of a good object oriented software design is much effective when it has highly maintainable class components. This paper describes an investigation into the use of indirect coupling to provide early indications of maintenance effort in object oriented software. The properties of interest are: (i) the potential maintainability of a class and (ii) the likelihood that a class will be affected by maintenance changes made to the overall system. The research explores that minimizing indirect coupling can provide useful indications of software maintenance effort that may have a significant influence on the effort during system maintenance and testing.

Measuring Maintenance Effort in Object Oriented Software with Indirect Coupling

Measurement of maintenance effort in object oriented software engineering is one of the major challenges. Coupling among classes is one of the major factors determining the maintenance effort. Coupling is measured as strength of interconnection or interdependence between different parts of the Classes in object oriented software. It is widely accepted that there is strong relationship between high coupling and poor maintainability. Indirect coupling which is transitive in nature manifests between two seemingly unrelated parts of the system through hidden connections plays a major role in determining maintenance effort. This research proposes a set of metrics which determines maintenance effort for software with Indirect Coupling. General Terms Software Quality, Software Engineering, Object Oriented Tesing.