258 research outputs found

    Understanding the Adoption of Mobile Data Services: A Value Perspective

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    Mobile data services (MDS) are wireless value-added pay-per-use services that have attracted increased attention in recent years. In the marketing and information system (IS) disciples, the ability of a service provider to offer a high level of value to its customers is regarded as a success. In this paper, a theoretical framework is proposed to investigate key drivers in wireless pay-per-use services behavior based on a value perspective. This study examines the role of three evaluation values, derived from marketing and IS literature, in adoption decisions. Potential adopters have no experience with MDS; thus, they likely conceive value based primarily on indirect experience with it, such as through advertisements or communication with peers. Most studies of MDS, however, have given little attention to the types of information sources that affect the formation of value that is obtained using MDS. In this study, the influence of members of social networks and secondary sources are regarded as the major sources of information. The proposed model is empirically tested using survey data collected from 287 potential adopters. The analysis results show that the proposed model, based on the aforementioned view of value, provides a significant explanation of the variance in the level of adoption intention toward MDS in individuals. The results of this study show that utilitarian and social values dominate adoption decisions while the impact of hedonic value in MDS acceptance is weaker than other values. Information from relevant others and from mass media play a critical role in forming the perceptions of value obtained from the use of MDS

    ReCrash: Making Crashes Reproducible

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    It is difficult to fix a problem without being able to reproduce it.However, reproducing a problem is often difficult and time-consuming.This paper proposes a novel algorithm, ReCrash, that generatesmultiple unit tests that reproduce a given program crash.ReCrash dynamically tracks method calls during every execution of the target program. If the program crashes, ReCrash saves information about the relevant method calls and uses the saved information to create unit tests reproducing the crash.We present reCrashJ an implementation of ReCrash for Java. reCrashJ reproducedreal crashes from javac, SVNKit, Eclipse JDT, and BST. reCrashJ is efficient, incurring 13%-64% performance overhead. If this overhead is unacceptable, then reCrashJ has another mode that has negligible overhead until a crash occurs and 0%-1.7% overhead until a second crash, at which point the test cases are generated
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