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In a competitive business landscape, large organizations such as insurance companies and banks are under high pressure to innovate, improvise and differentiate their products and services while continuing to reduce the time-to market for new product introductions. Generating a single view of the customer is critical from different perspectives of the systems developer over a period of time because of the existence of disconnected systems within an enterprise. Therefore, to increase revenues and cost optimization, it is important build enterprise systems more closely with the business requirements by reusing the existing systems. While building distributed based applications, it is important to take into account the proven processes like Rational Unified Process (RUP) to mitigate the risks and increase the reliability of systems. Experiences in developing applications in Java Enterprise Edition (JEE) with customized RUP have been presented in this paper. RUP is adopted into an onsite-offshore development model along with ISO 9001 and SEI CMM Level 5 standards. This paper provides an RUP approach to achieve increased reliability with higher productivity and lower defect density along with competitiveness through cost effective custom software solutions. Early qualitative software reliability prediction is done using fuzzy expert systems, using which the expected number of defects in the software prior to the experimental testing is obtained. The predicted results are then compared with the practical values obtained during the actual testing procedure.

Demand for highly reliable software is increasing day by day which in turn has increased the pressure on the software firms to provide reliable software in no time. Ensuring high reliability of the software can only be done by prolonged testing which in result consumes more resources which is not feasible in the existing market situation. To overcome this, software firms are providing patches after software release so as to fix the remaining number of bugs and to give better product experience to users. An update/fix is a minor portion of software to repair the bugs. With such patches, organizations enhance the performance of the software. Delivering patches after release demands extra effort and resources which are costly and hence not economical for the firms. Also, early patch release might cause improper fixation of bugs, on the other hand, delayed release may increase the chances of more failure during the operational phase. Therefore, determining optimal patch release time is imperative. To overcome the above issues we have formulated a two-dimensional time and effort-based cost model to regulate the optimum release and patch time of software, so that the total cost is minimized. Proposed model is validated on a real life data set.

Testing life cycle poses a problem of achieving a high level of software reliability while achieving an optimal release time for the software. To enhance the reliability of the software, retain the market potential for the software and reduce the testing cost, the enterprise needs to know when to release the software and when to stop testing. To achieve this, enterprises usually release their product earlier in market and then release patches subsequently. Software patching is a process through which enterprises debug, update, or enhance their software. Software patching when used as a debugging process ensures an optimal release for the product, increasing the reliability of the software while reducing the economic overhead of testing. Today, due to the diverse and distributed nature of software, its journey in the market is dynamic, making patching an inherent aspect of testing. A patch is a piece of software designed to update a computer program or its supporting data to fix or improve it. Researchers have worked in the field to minimize the testing cost, but so far, reliability has not been considered in the models for optimal time scheduling using patching. In this paper, we discuss reliability, which is a major attribute of the quality of software. Thus, to address the issues of testing cost, release time of software, and a desirable reliability level, we propose a reliability growth model implementing software patching to make the software system reliable and cost effective. The numeric illustration has been implemented using real-life software failure data set.

This paper presents a multi-stage software design approach for fault-tolerance. In the first stage, a formalism is introduced to represent the behavior of the system by means of a set of assertions. This formalism enables an execution tree (ET) to be generated where each path from the root to the leaf is, in fact, a well-defined formula. During the automatic generation of the execution tree, properties like completeness and consistency of the set of assertions can be verified and consequently design faults can be revealed. In the second stage, the testing strategy is based on a set of WDFs. This set represents the structural deterministic test for the model of the software system and provides a framework for the generation of a functional deterministic test for the code implementation of the model. This testing strategy can reveal the implementation faults in the program code. In the third stage, the fault-tolerance of the software system against hardware failures is improved in a way such that the design and implementation features obtained from the first two stages are preserved. The proposed approach provides a high level of user-transparency by employing object-oriented principles of data encapsulation and polymorphism. The reliability of the software system against hardware failures is also evaluated. A tool, named Software Fault-Injection Tool (SFIT), is developed to estimate the reliability of a software system.

For prediction or verification of system reliability, it is often necessary to conduct individual tests of components that comprise the system. The question then arises as to how the total test efforts should be allocated among different components so as to minimize test costs. This paper describes the role of mathematical programming in obtaining the optimum test plans. The problem is formulated on the notion of producer’s and consumer’s risks in traditional acceptance sampling plans. Examples are given for different distributions of component failure times and for a series and a parallel system.

This paper presents design and performance of a prototype of new humanoid arm that has been developed at the LARM2 laboratory of the University of Rome “Tor Vergata”. This new arm, called LARMbot PK arm, is an upper limb that is designed for the LARMbot humanoid robot. LARMbot is a humanoid robot designed to move freely in open spaces, and able to adapt to task environment. Its objective is to transport objects weighing a few kilograms in order to facilitate the restocking of workstations, or to manage small warehouses and other tasks feasible for humanoids. The LARMbot PK arm is conceived as a solution that is designed on the basis of a parallel tripod structure using linear actuators to provide high agility of movement. This solution is designed with components that can be found on the market or can be created by 3D printing in order to offer a quality and price ratio well convenient for user-oriented humanoid robots. Experimental tests are discussed with the built prototype to demonstrate the capabilities of the proposed solution in terms of agility, autonomy, and power to validate the LARMbot PK arm solution as a satisfactory solution for the new upper limbs of the LARMbot humanoid robot.

This paper analyzes the source and the characterization method of white noise in FOCT, researches the statistical properties of white noise in FOCT while the equipment is in a zero-input current environment. Data in time-domain and frequency-domain is analyzed and compared under different primary input current. The result indicates that white noise in FOCT accords with a normal distribution with mean zero, and the noise magnitude is independent of the primary current value. On that basis, we research how the white noise affects the test result of FOCT and provide an effective method to reduce the impact.