33488472
Expert System Assisted Test Data Generation for Software Branch Coverage
Abstract With the increased production of complex software systems, verification and validation (V & V) has evolved into a set of activities that span the entire software life cycle. Among these various activities, software testing plays a major role in V&V. Conventional software testing methods generally require considerable manual effort which can generate only a limited number of test cases before the amount of time expended becomes unacceptably large. In this paper, we present a new approach to generating test cases based on artificial intelligence methods. By analyzing the branch coverage of previous test cases, an expert system is able to generate new test cases which provide additional coverage. Heuristic rules are used to modify previous test cases in order to achieve the desired branch coverage. This approach to software testing has the potential for greatly reducing the overall costs associated with branch coverage testing.
3504482
An Intelligent Test Data Generator for Software Branch Coverage
317687
A Cost Model for Determining the Optimal Number of Software Test Cases
A probabilistic model is presented that demonstrates the optimal number of software test cases required in situations where the following can be estimated as independent parameters: (1) the cost per test; (2) the cost per error if undetected until field implementation; (3) the number of software executions over its lifetime; (4) the number of possible different executions; and (5) the number of faults embedded in the software. A formula is derived by the use of calculus and is solved by approximation techniques. Tables of the optimal number of tests over a range of parameter values are presented to illustrate the results. The model serves as a basis for further research efforts to improve the accuracy of input variable estimation. >
1207779
Experience in Teaching a Management-Oriented Capstone Software Engineering Course
Many computer science departments teach a capstone software engineering course involving the design and implementation of a large-scale project. Such a course is normally taught with students working together in teams; consequently, students must face a number of problems related to project management and team dynamics. Our experience has been that students frequently fail to adequately cope with these organizational problems, and consequently fail to complete their projects at an acceptable level of quality. To prepare students to better face these problems, we have modified our capstone software engineering course to provide equal emphasis in both management and technical areas. Our approach to management topics is formal rather than anecdotal, stressing general principles applied to organizational problems arising specifically from situations that occur frequently in technical organizations. This paper reports on the structure of this course, and provides insight into our initial experience in teaching it.
18888101
Validation of Elliptic Curve Public Keys
We present practical and realistic attacks on some standardized elliptic curve key establishment and public-key encryption protocols that are effective if the receiver of an elliptic curve point does not check that the point lies on the appropriate elliptic curve. The attacks combine ideas from the small subgroup attack of Lim and Lee, and the differential fault attack of Biehl, Meyer and Muller. Although the ideas behind the attacks are quite elementary, and there are simple countermeasures known, the attacks can have drastic consequences if these countermeasures are not taken by implementors of the protocols. We illustrate the effectiveness of such attacks on a key agreement protocol recently proposed for the IEEE 802.15 Wireless Personal Area Network (WPAN) standard.
7484630
A Graduate Level Expert Systems Course
This article presents an approach to a graduate-level course in expert, knowledge-based, problem-solving systems. The core of the course, and this article, is a set of questions called a profile, that can be used to characterize and compare each system studied.
16238835
Spatial agent‐based modelling
The convergence of object-oriented approaches to data modelling within geographic information science together with increasingly fine-scale data collection approaches and discrete-event simulations has created new opportunities to build dynamic representations of geographical systems (Gimblett 2002, Brown et al. 2005). In particular, agent-based modelling has become an important representational paradigm within both the biological (DeAngelis and Gross 1992) and social (Epstein and Axtell 1996) sciences. A software agent can be constructed as a selfdirected object, i.e. it has the ability to satisfy internal goals or objectives through actions and decisions based on a set of internal rules or strategies (Iglesias et al. 1999) and can be used in one of two primary modes: instrumental and representational. In the instrumental mode, agents are created for the primary purpose of performing a computing task to reduce reliance on the attention and cognition of a human operator, i.e. the agents stand in for the computer user. A good example is the system described by Sengupta and Bennett (2003) that uses agents to assist new users of geographic information systems in their application for decision support. In representational mode, the agent is designed for the primary purpose of behaving in a manner that is consistent with that of a third party, i.e. another person, group, institution, animal, or other animate object. Although this distinction is somewhat arbitrary and, in practice, not always clear, it highlights the range of purposes to which agent-based modeling is put within the articles presented here. This special issue draws together six papers that were presented at the GeoComputation 2005 conference, held on 1–3 August 2005 in Ann Arbor, Michigan and jointly hosted by the School of Natural Resources and Environment at the University of Michigan and the Institute for Geospatial Research and Education at Eastern Michigan University. As we surveyed the themes of papers presented at the conference, agent-based modelling was clearly a dominant one. Though the papers here tended to focus on issues associated with using agent-based modelling in representational mode, a couple of papers hinted at instrumental uses. For example, Parunak et al. discuss how agents can be used to solve the problems of navigation in heterogeneous landscapes, largely an instrumental application in which the agents perform computations collectively to solve complex spatial problems. Graniero and Robinson present a framework for building coupled agentlandscape models and illustrate the framework with representational agent-based
13541175
Evaluating Network Serviceability
Abstract The capability to manage network operations on a day-to-day basis has become an important area of concern given the rapid expansion of computer networks. A related, but much less studied area, is the impact that the design of a network has on the ease with which it can be serviced. Evaluating the ease of servicing the network and its components does not concentrate on day-to-day operations of the network, but rather examines the network design over a longer term to identify problematic components, configurations and dependencies between components based on expert knowledge and historical data. This paper reports on our experience with a system to evaluate the ease of servicing a network—its serviceability—given a description of its design. The motivation for the work is that computer networks are more often “grown” than “designed” without concern for serviceability issues. The work also examines the impact of dependencies between components on the role of service and the potential disruption costs caused by these dependencies. This work is important because it is pro-active in explicitly considering the role of servicing a network when changing the components or configuration of a network. This approach is in contrast to network management, which is reactive in dealing with problems. The paper reports on a successful implementation of such as system and our experiences with it.
29206629
Inferring User Interest
As the World Wide Web continues to grow, people find it impossible to access even a small portion of the information generated in a day from Usenet news, e-mail, and Web postings. Automated filters help us to prioritize and access only the information in which we're interested. Because opinions differ about the importance or relevance of information, people need personalized filters. Implicit indicators captured while users browse the Web can be as predictive of interest levels as explicit ratings.