Current Issue : July - September Volume : 2016 Issue Number : 3 Articles : 4 Articles
The common assumption for most existing\nsoftware reliability growth models is that fault is independent\nand can be removed perfectly upon detection. However,\nit is often not true due to various factors including software\ncomplexity, programmer proficiency, organization hierarchy,\netc. In this paper, we develop a software reliability model\nwith considerations of fault-dependent detection, imperfect\nfault removal and the maximum number of faults software.\nThe genetic algorithm (GA) method is applied to estimate\nthe model parameters. Four goodness-of-fit criteria, such as\nmean-squared error, predictive-ratio risk, predictive power,\nand Akaike information criterion, are used to compare the\nproposed model and several existing software reliability\nmodels. Three datasets collected in industries are used to\ndemonstrate the better fit of the proposed model than other\nexisting software reliability models based on the studied criteria....
Software innovation, the ability to produce novel and useful software systems, is an important capability for software development\norganizations and information system developers alike. However, the software development literature has traditionally focused\non automation and efficiency while the innovation literature has given relatively little consideration to the software development\ncontext. As a result, there is a gap in our understanding of how software product and process innovation can be managed.\nSpecifically, little attention has been directed toward synthesizing prior learning or providing an integrative perspective on the\nkey concepts and focus of software innovation research. We therefore identify 93 journal articles and conference papers within\nthe domain of software innovation and analyse repeating patterns in this literature using content analysis and causal mapping.We\nidentify drivers and outputs for software innovation and develop an integrated theory-oriented concept map.We then discuss the\nimplications of this map for future research....
Combinatorial testing (CT) technique could significantly reduce testing cost and increase software system quality. By using the test\nsuite generated by CT as input to conduct black-box testing towards a system, we are able to detect interactions that trigger the\nsystem�s faults. Given a test case, there may be only part of all its parameters relevant to the defects in system and the interaction\nconstructed by those partial parameters is key factor of triggering fault. If we can locate those parameters accurately, this will\nfacilitate the software diagnosing and testing process. This paper proposes a novel algorithm named complete Fault Interaction\nLocation (comFIL) to locate those interactions that cause system�s failures and meanwhile obtains the minimal set of target\ninteractions in test suite produced by CT. By applying this method, testers can analyze and locate the factors relevant to defects\nof system more precisely, thus making the process of software testing and debugging easier and more efficient. The results of our\nempirical study indicate that comFIL performs better compared with known fault location techniques in combinatorial testing\nbecause of its improved effectiveness and precision....
The quality of the software product is a crucial factor that contributes to its success. Therefore, it\nis important to specify the right software quality requirements that will establish the basis for\ndesired quality of the final system/software product. There are several known methodologies/\nprocesses that support the specification of the system/software functional requirements starting\nfrom the user needs to finally obtain the system requirements that the developers can implement\nthrough their development process. System/software quality requirements are interdependent\nwith functional requirements, which means that the system/software quality requirements are\nmeant to be specified in parallel with the latter. The ISO/IEC 25000 [1] SQuaRE series of standards\ninclude the standard ISO/IEC 25030ââ?¬â?Software engineeringââ?¬â?Software Quality Requirements and\nEvaluationââ?¬â?Quality requirements [2], which has as main goal to help specify software quality\nrequirements. As to date, this standard does not offer clear and concise steps that a software\nquality engineer could follow in order to specify them. This article presents modifications recommended\nfor ISO/IEC 25030 standard, with, among the others, a new requirements definition process\nthat allows for specifying the system/software quality requirements taking into account the\nexisting published system and software quality model ISO/IEC 25010 [3] as well as all the stakeholders\nof the project....
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