References of "IEEE Transactions on Software Engineering"
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See detailOn the Effectiveness of Contracts as Test Oracles in the Detection and Diagnosis of Functional Faults in Concurrent Object- Oriented Software
Araujo, Wladimir; Briand, Lionel UL; Labiche, Yvan

in IEEE Transactions on Software Engineering (2014), 40(10), 971-992

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See detailStatic Analysis for Extracting Permission Checks of a Large Scale Framework: The Challenges And Solutions for Analyzing Android
Bartel, Alexandre; Klein, Jacques UL; Monperrus, Martin et al

in IEEE Transactions on Software Engineering (2014), 40(6), 617-632

A common security architecture is based on the protection of certain resources by permission checks (used e.g., in Android and Blackberry). It has some limitations, for instance, when applications are ... [more ▼]

A common security architecture is based on the protection of certain resources by permission checks (used e.g., in Android and Blackberry). It has some limitations, for instance, when applications are granted more permissions than they actually need, which facilitates all kinds of malicious usage (e.g., through code injection). The analysis of permission-based framework requires a precise mapping between API methods of the framework and the permissions they require. In this paper, we show that naive static analysis fails miserably when applied with off-the-shelf components on the Android framework. We then present an advanced class-hierarchy and field-sensitive set of analyses to extract this mapping. Those static analyses are capable of analyzing the Android framework. They use novel domain specific optimizations dedicated to Android. [less ▲]

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See detailGenerating Test Data from OCL Constraints with Search Techniques
Ali, Shaukat; Iqbal, Zohaib; Arcuri, Andrea UL et al

in IEEE Transactions on Software Engineering (2013), 39(10),

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See detailMatching and Merging of Variant Feature Specifications.
Nejati, Shiva UL; Sabetzadeh, Mehrdad UL; Chechik, Marsha et al

in IEEE Transactions on Software Engineering (2012), 38(6), 1355-1375

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See detailFormal Analysis of the Probability of Interaction Fault Detection Using Random Testing
Arcuri, Andrea UL; Briand, Lionel UL

in IEEE Transactions on Software Engineering (2012), 38(5), 1088-1099

Modern systems are becoming highly configurable to satisfy the varying needs of customers and users. Software product lines are hence becoming a common trend in software development to reduce cost by ... [more ▼]

Modern systems are becoming highly configurable to satisfy the varying needs of customers and users. Software product lines are hence becoming a common trend in software development to reduce cost by enabling systematic, large-scale reuse. However, high levels of configurability entail new challenges. Some faults might be revealed only if a particular combination of features is selected in the delivered products. But testing all combinations is usually not feasible in practice, due to their extremely large numbers. Combinatorial testing is a technique to generate smaller test suites for which all combinations of t features are guaranteed to be tested. In this paper, we present several theorems describing the probability of random testing to detect interaction faults and compare the results to combinatorial testing when there are no constraints among the features that can be part of a product. For example, random testing becomes even more effective as the number of features increases and converges toward equal effectiveness with combinatorial testing. Given that combinatorial testing entails significant computational overhead in the presence of hundreds or thousands of features, the results suggest that there are realistic scenarios in which random testing may outperform combinatorial testing in large systems. Furthermore, in common situations where test budgets are constrained and unlike combinatorial testing, random testing can still provide minimum guarantees on the probability of fault detection at any interaction level. However, when constraints are present among features, then random testing can fare arbitrarily worse than combinatorial testing. As a result, in order to have a practical impact, future research should focus on better understanding the decision process to choose between random testing and combinatorial testing, and improve combinatorial testing in the presence of feature constraints. [less ▲]

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