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Today's complex software systems consist of several components that interact in complex ways to provide services to users. In doing so, these systems go through continuous assessment of their context and configure themselves accordingly to keep user satisfaction high. A popular approach to design adaptive software systems is to perform variability modelling, for instance adopting a feature-based approach...
Software systems are designed to support their users in performing tasks that are parts of more general processes. Unfortunately, software designers often make invalid assumptions about the users' processes and therefore about the requirements to support such processes. Eliciting and validating such assumptions through manual means (e.g., through observations, interviews, and workshops) is expensive,...
Gamification has been applied in software engineering contexts, and more recently in requirements engineering with the purpose of improving the motivation and engagement of people performing specific engineering tasks. But often an objective evaluation that the resulting gamified tasks successfully meet the intended goal is missing. On the other hand, current practices in designing gamified processes...
Automated decision-making techniques are useful to support engineers when performing requirements engineering tasks. However, to be effectively used in practice they need to be integrated into the organisational context, in which stakeholder engagement becomes a critical adoption factor. In this paper, we propose a tool-supported collaborative requirements prioritisation process, called GRP, which...
Automated generation of system level tests for grammar based systems requires the generation of complex and highly structured inputs, which must typically satisfy some formal grammar. In our previous work, we showed that genetic programming combined with probabilities learned from corpora gives significantly better results over the baseline (random) strategy. In this work, we extend our previous work...
Evo Suite-MOSA is a unit test data generation tool that employs a novel many-objective optimization algorithm suitably developed for branch coverage. It was implemented by extending the Evo Suite test data generation tool. In this paper we present the results achieved by Evo Suite-MOSA in the third Unit Testing Tool Competition at SBST'15. Among six participants, Evo Suite-MOSA stood third with an...
Test data generation has been extensively investigated as a search problem, where the search goal is to maximize the number of covered program elements (e.g., branches). Recently, the whole suite approach, which combines the fitness functions of single branches into an aggregate, test suite-level fitness, has been demonstrated to be superior to the traditional single-branch at a time approach. In...
To isolate and fix failures that occur in the field, after deployment, developers must be able to reproduce and investigate such failures in-house. In practice, however, bug reports rarely provide enough information to recreate field failures, thus making in-house debugging an arduous task. This task becomes even more challenging for programs whose input must adhere to a formal specification, such...
Reproducing field failures in-house, a step developers must perform when assigned a bug report, is an arduous task. In most cases, developers must be able to reproduce a reported failure using only a stack trace and/or some informal description of the failure. The problem becomes even harder for the large class of programs whose input is highly structured and strictly specified by a grammar. To address...
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