Earticle

Passive testing is an alternative testing approach whose purpose is to passively analyze an implementation behaviour without disturbing it. Usually, passive testing methods extract traces by means of snier-based tools, running in the same environment as the implementa- tion. Nevertheless, many implementation environments prevent from setting a snier-based tool for security or technical reasons. We propose a passive testing method based on the notion of proxy-tester which represents an intermediary between client applications and the implementation. We dene a proxy-tester as a product between the specication and its canonical tester, which is able to receive the client trac and to forward it to the imple- mentation and vice versa. It also aims to analyze the implementation traces to detect faults. We dene a non conformance relation between the implementation, its specication and the external environment from which is received the client trac. We also provide some pre- liminary results on the Amazon E-commerce Web service and discuss about the proxy-tester benets.

Tracking of a reported bug for fixing is a fascinating area of research in software engineering. Many open source, free and commercial bug tracking tools have been developed and are currently under development. The industry needs criteria to select the best tool among the available set of tools that will help in fixing and tracking the progress of bug fixes. In this paper, we use BugZilla, Jira, Trac, Mantis, BugTracker.Net, Gnats and Fossil for comparative study. We present a comprehensive classification criteria to review the available tools and propose a new tool named Bug Tracking and Reliability Assessment System (BTRAS) for the bug tracking/reporting and reliability assessment. BTRAS helps in reporting the bug, assigning the bug to the developer for fixing, monitoring the progress of bug fixing by various graphical/charting facility and status updates, providing reliability bug prediction and bug complexity measurements, and distributing fixes to users/developers.

The back propagation (BP) algorithm is a very popular learning approach in multilayer feedforward networks. However, the most serious problems associated with the BP are local minima problem and slow convergence speeds. Over the years, many improvements and modifications of the BP learning algorithm have been reported. In this research, we propose a new modified BP learning algorithm by introducing adaptive gain together with adaptive momentum and adaptive learning rate into weight update process. By computer simulations, we demonstrate that the proposed algorithm can give a better convergence rate and can find a good solution in early time compare to the conventional BP. We use four common benchmark classification problems to illustrate the improvement in convergence time.

Embedded systems are used in many critical applications of our daily life. The increased complexity of embedded systems and the tightened safety regulations posed on them and the scope of the environment in which they operate are driving the need of more dependable embedded systems. Therefore, achieving a high level of quality and dependability to embedded systems is an ultimate goal. This research study investigates the inter-relationships between dependability and other embedded systems quality attributes using two pieces of information: Tactics and Dependability Quality attributes scenarios.

Distributed wireless sensor network technologies have become one of the major research areas in healthcare industries due to rapid maturity in improving the quality of life. The implementation of ubiquitous healthcare systems provides rich contextual information and warning mechanisms against abnormal conditions with continual and remote monitoring of patients. This minimizes the need for healthcare professionals and helps the ill and elderly to survive an independent life as well as aid stationary and mobile patients in preventive medicine. This research studies the deployment of distributed wireless sensors networks for monitoring of patients and report tracking to central database server containing patient vital information. This study performs optimization scheme for optimal placement of wireless sensors and movement coordination techniques within the patient monitoring area where patients can be mobile as they perform their daily activities. A movement tracking algorithm is proposed for better patient report tracking techniques and aid in optimal deployment of wireless sensor networks. Results show that wireless sensors can be exploited for better application of preventive medicine and improve the network coverage of the patient being monitored and tracked.

E-learning is taking more roles in the current methods of education. The automatic grading and assessment play a major role in both e-learning and traditional education as a method to reduce educational expenses and relief instructors from some of the lengthy tasks such as grading. In this paper, automatic grading for software code assignments or homework is described. A tool is developed to automatically grade students’ code assignments. Concepts or code from Students’ answers are first parsed. Key abstractions and keywords are extracted from students’ assignments and compared with typical or expected answers. Weights are given to code keywords by the instructor based on their value and importance in the overall answer. Relating this grading with code plagiarism, similarities are also measured between students’ assignments and an Euclidean distance method is developed and calculated between each assignment with all other assignments. Results showed that automatic grading for code assignments can be automated due to the nature of expected answers where grader can set and expect a fixed number of possible keywords in each answer. Such formality may not exist for several other types of essay questions.

Abuse case has great support in identifying security threats and security requirements caused by outside attackers, but it has not been used to capture non-malicious deliberate acts for safety concerns that involves inside abusers. It is important to represent inside abusers in a model and distinguish them from inside intruders and outside attackers, since their behaviors are different. The intent of this paper is to propose a new extension of abuse case to identify deliberate acts of safety threats caused by inside abusers. A new notation vulnerable use case was introduced to express the actions that leads to threats from inside abusers, countermeasures were introduced by safety use cases, and new relationships were defined to clarify the interactions among use cases, vulnerable use cases, safety use cases and abuse cases. This enhanced model provided a way of capturing as much potential risks caused by inside abusers, and embed safety requirements in the early stage of the system development life cycle.

The design of an information system for a business process can be implemented either in the object-oriented paradigm or in relational database management system as per the client’s choice. In object oriented paradigm, the design starts with abstraction of objects, classes, attributes, functional dependencies, interrelationships and use cases but in relational database management system (RDBMS) the abstractions may be in the form of entity, attributes, interrelationships, functional dependencies and functionalities. These abstracted view elements are analogous to each other with nomenclature change e.g. view element entity of a RDBMS is analogous to object/class of an Object Technology. The pragmatic practice of designing a relation or class/object of an information system is modeled with Unified Modeling Language (UML) by human intervention. Further, the structuring and grouping of an attributes for a class/object or entity in a design is made possible by the intuition of a designer, which may lead to the error discretions. This paper proposes a realizable methodology that accepts the attributes and the functional dependencies abstracted from the Software Requirements Specifications (SRS) and trims them using minimal cover of functional dependencies to the form of a dependency matrix. The representation is used to refine the functional dependencies that exist among the attributes of each class/entity and grouping them for a relation or object/class by using the normalization process. The procedure is automated to eliminate possible human errors discretions and the correctness and completeness is authenticated through the amalgamation of axiom in the methodology.

In the 24/7 web industry, business owners can feel a constant need to push the latest and greatest software to the live site in order to remain competitive and ensure growth. However, the bottom line to the business must always be that the site is fully available and functional to consumers. The business cannot make money if a customer is greeted with a maintenance page. Also, the business reputation of the company can be severely damaged if the web site proves to be unavailable to customers or if orders aren’t received due to improper fulfillment. The constant rapid updating and changing of software can cause severe site instability to the point where the business can fail. Systems integration engineers are often the last line of defense in preventing this type of catastrophic failure. Due to the need for rapid software integration, a heuristic for quantitatively measuring risk in the system is invaluable to determine what software is riskiest to deploy and where problems are most likely to occur. The software deployment risk assessment heuristic presented in this paper allows systems integration engineers to determine where these risks are most apparent in the system and to explore where best to focus their efforts for ensuring the least disruptive deployment method for live production systems.

Software refactoring is a collection of reengineering activities that aims to improve software quality. Refactorings are commonly used in agile software processes to improve software quality after a significant software development or evolution. There is belief that refactoring improves quality factors such as understandability, flexibility, and reusability. However, there is limited empirical evidence to support such assumptions. The aim of this study is to confirm such claims using a hierarchal quality model. We study the effect of software refactoring on software quality. We provide details of our findings as heuristics that can help software developers make more informed decisions about what refactorings to perform in regard to improve a particular quality factor. We validate the proposed heuristics in an empirical setting on two open-source systems. We found that the majority of refactoring heuristics do improve quality; however some heuristics do not have a positive impact on all software quality factors. In addition, we found that the impact analysis of refactorings divides software measures into two categories: high and low impacted measures. These categories help in the endeavor to know the best measures that can be used to identify refactoring candidates. We validated our findings on two open-source systems—Eclipse and Struts. For both systems, we found consistency between the heuristics and the actual refactorings.

In Global markets the competition has increased dramatically. This has resulted on the need for software development firms to produce at a lower cost, with higher quality and within shorter time frames. The focus must clearly be put on the customer and the objective must not simply be to satisfy, but to delight. This can only be accomplished by providing the right system and executing the pertinent project(s) in the right way. In industry, information on defect density of a product tends to become available too late in the software development process to affordably guide corrective actions. An important step towards remediation of the problem associated with this late information lies in the ability to provide an early estimation of defect density. The residual defect density of a software product can often only be estimated, based on the number of user complaints. The number of complaints does not just depend on the residual defect density, it also depends on the number of users, and the amount and duration of actual usage. The identification and removal of software defects constitutes the basis of the software testing process, a fact that inevitably places increased emphasis on defect related software measurements. The stochastic parameters of the proposed system with specific system boundaries under a given environment have been estimated using simulation.

Component-Based Software Engineering (CBSE) is a knowledge-intensive discipline where all activities require the use and the transfer of knowledge between collaborators. A better usage, transfer and application of this knowledge are required factors to face the challenges of CBSE. In this perspective, Knowledge Management (KM) aims at setting up knowledge-focused processes in the organization. Knowledge Management Systems (KMS) are the technological infrastructure supporting these processes. In this paper, we present a new methodology of KMS implementation in a CBSE-oriented organization. We also present a case study of applying this methodology in an existing CBSE organization.

A number of different factors are thought to influence the efficiency of the software development process. These include programming languages, use of formal methodologies, CASE tools, etc. Moreover, efficiency in the context of software development has traditionally been measured as the ratio of functionality, either lines of code or functions points, and the effort expended. This is a unidimensional measure and ignores factors such as quality and elapsed time. This study utilizes Data Envelopment Analysis (DEA) to develop a multidimensional measure of efficiency in the context of software development and then examines how efficiency varies with other influencing factors such as the use of CASE tools, use of methodologies, team size, application type, etc. using a decision tree based model.