A decision model for agile software release

Wang, Xiaohua; Zou, Li‐Ping

doi:10.1109/icrms.2011.5979368

Cited by 2 publications

(1 citation statement)

References 12 publications

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“…Next, the concept of attack ability is proposed by item response theory and the discrimination of threat of attack is improved. Following this, with the three-demarcation analytic hierarchy process [12] to calculate the service weight of importance, the accuracy will be improved. The last, the risk situation graph of service, host, and network logic layer are draw by analyzing each layer of the risk situation.…”

Section: Introductionmentioning

confidence: 99%

Network Security Risk Assessment Based on Item Response Theory

Li¹,

Qing²,

Zhu³

et al. 2015

Proceedings of the 8th International Conference on Mobile Multimedia Communications

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Owing to the traditional risk assessment method has onesidedness and is difficult to reflect the real network situation, a risk assessment method based on Item Response Theory (IRT) is put forward in network security. First of all, the novel algorithms of calculating the threat of attack and the successful probability of attack are proposed by the combination of IRT model and Service Security Level. Secondly, the service weight of importance is calculated by the three-demarcation analytic hierarchy process. Finally, the risk situation graph of service, host and network logic layer could be generated by the improved method. The simulation results show that this method can be more comprehensive consideration of factors which are affecting network security, and a more realistic network risk situation graph in real-time will be obtained.

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Section: Introductionmentioning

confidence: 99%

Network Security Risk Assessment Based on Item Response Theory

Li¹,

Qing²,

Zhu³

et al. 2015

Proceedings of the 8th International Conference on Mobile Multimedia Communications

View full text Add to dashboard Cite

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Mechanism for on demand Tag-Based software testing in virtualized environments

Gopularam¹,

Yogeesha

2012

2012 Fourth International Conference on Advanced Computing (ICoAC)

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Software development life cycle consists of various stages like requirements, design, implementation, testing and maintenance. In a typical enterprise level project number of testcases to be executed for each release would be in thousands. One known way of segregating the testcases is using component or module names and one can also classify them based on level of importance like unit testing, functional, sanity etc. With iterative development models like Agile, the release cycle is short and it is prudent to execute the testcase selectively majorly concentrating on impacting components.In this paper we provide a generic way to manage the tests and provide an efficient mechanism to run the tests selectively. In our approach we make use of well-known build management tool called Jenkins for running the tests on-demand. One unique benefit of our approach is that the input is a single commaseparated-value (CSV) file and it is very easy to add/modify existing tests. The tests are tagged using well known keywords (viz. database-layer, configuration, regression). When some particular tests need to be run, the user enters 'Tag' in the job parameter and testsuite will be generated dynamically.In this paper we also describe an end-to-end test management system that supports running selective tests with help of jobs created in Jenkins environment. The proposed model of Tests execution is highly useful in high demanding environments like agile software development model, Test driven development model where feature development is many times faster than traditional water fall model. The approach suggested in this paper makes optimum use of cloud resources by distributing the jobs, so this can be utilized specially for testing under virtualized environment.

show abstract

A decision model for agile software release

Cited by 2 publications

References 12 publications

Network Security Risk Assessment Based on Item Response Theory

Network Security Risk Assessment Based on Item Response Theory

Mechanism for on demand Tag-Based software testing in virtualized environments

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