158,095 research outputs found
Variability and Evolution in Systems of Systems
In this position paper (1) we discuss two particular aspects of Systems of
Systems, i.e., variability and evolution. (2) We argue that concepts from
Product Line Engineering and Software Evolution are relevant to Systems of
Systems Engineering. (3) Conversely, concepts from Systems of Systems
Engineering can be helpful in Product Line Engineering and Software Evolution.
Hence, we argue that an exchange of concepts between the disciplines would be
beneficial.Comment: In Proceedings AiSoS 2013, arXiv:1311.319
Time-Space Efficient Regression Testing for Configurable Systems
Configurable systems are those that can be adapted from a set of options.
They are prevalent and testing them is important and challenging. Existing
approaches for testing configurable systems are either unsound (i.e., they can
miss fault-revealing configurations) or do not scale. This paper proposes
EvoSPLat, a regression testing technique for configurable systems. EvoSPLat
builds on our previously-developed technique, SPLat, which explores all
dynamically reachable configurations from a test. EvoSPLat is tuned for two
scenarios of use in regression testing: Regression Configuration Selection
(RCS) and Regression Test Selection (RTS). EvoSPLat for RCS prunes
configurations (not tests) that are not impacted by changes whereas EvoSPLat
for RTS prunes tests (not configurations) which are not impacted by changes.
Handling both scenarios in the context of evolution is important. Experimental
results show that EvoSPLat is promising. We observed a substantial reduction in
time (22%) and in the number of configurations (45%) for configurable Java
programs. In a case study on a large real-world configurable system (GCC),
EvoSPLat reduced 35% of the running time. Comparing EvoSPLat with sampling
techniques, 2-wise was the most efficient technique, but it missed two bugs
whereas EvoSPLat detected all bugs four times faster than 6-wise, on average.Comment: 14 page
Market-based Recommendation: Agents that Compete for Consumer Attention
The amount of attention space available for recommending suppliers to consumers on e-commerce sites is typically limited. We present a competitive distributed recommendation mechanism based on adaptive software agents for efficiently allocating the 'consumer attention space', or banners. In the example of an electronic shopping mall, the task is delegated to the individual shops, each of which evaluates the information that is available about the consumer and his or her interests (e.g. keywords, product queries, and available parts of a profile). Shops make a monetary bid in an auction where a limited amount of 'consumer attention space' for the arriving consumer is sold. Each shop is represented by a software agent that bids for each consumer. This allows shops to rapidly adapt their bidding strategy to focus on consumers interested in their offerings. For various basic and simple models for on-line consumers, shops, and profiles, we demonstrate the feasibility of our system by evolutionary simulations as in the field of agent-based computational economics (ACE). We also develop adaptive software agents that learn bidding strategies, based on neural networks and strategy exploration heuristics. Furthermore, we address the commercial and technological advantages of this distributed market-based approach. The mechanism we describe is not limited to the example of the electronic shopping mall, but can easily be extended to other domains
Achieving Effective Innovation Based On TRIZ Technological Evolution
Organised by: Cranfield UniversityThis paper outlines the conception of effective innovation and discusses the method to achieve it. Effective
Innovation is constrained on the path of technological evolution so that the corresponding path must be
detected before conceptual design of the product. The process of products technological evolution is a
technical developing process that the products approach to Ideal Final Result (IFR). During the process, the
sustaining innovation and disruptive innovation carry on alternately. By researching and forecasting potential
techniques using TRIZ technological evolution theory, the effective innovation can be achieved finally.Mori Seiki ā The Machine Tool Compan
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