Systematic Engineering of Mutation Operators.

Gómez‐Abajo, Pablo; Guerra, Esther; Lara, Juan de; Merayo, Mercedes G.

doi:10.5381/jot.2020.19.3.a5

Cited by 2 publications

(2 citation statements)

References 31 publications

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“…Given a WODEL program, the synthesizer generates models over which all mutation operators in the program are applicable [9,10]. The generation is based on model search, a technique that applies constraint resolution over models [28].…”

Section: Generation Of Exercises Via Seed Model Synthesismentioning

confidence: 99%

Automated generation and correction of diagram‐based exercises for Moodle

Gómez‐Abajo,

Guerra,

de Lara

2023

Comp Applic In Engineering

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One of the most time‐consuming task for teachers is creating and correcting exercises to evaluate students. This is normally performed by hand, which incurs high time costs and is error‐prone. A way to alleviate this problem is to provide an assistant tool that automates such tasks. In the case of exercises based on diagrams, they can be represented as models to enable their automated model‐based generation for any target environment, like web or mobile applications, or learning platforms like Moodle. In this paper, we propose an automated process for synthesizing five types of diagram‐based exercises for the Moodle platform. Being model‐based, our solution is domain‐agnostic (i.e., it can be applied to arbitrary domains like automata, electronics, or software design). We report on its use within a university course on automata theory, as well as evaluations of generality, effectiveness and efficiency, illustrating the benefits of our approach.

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Section: Generation Of Exercises Via Seed Model Synthesismentioning

confidence: 99%

Automated generation and correction of diagram‐based exercises for Moodle

Gómez‐Abajo,

Guerra,

de Lara

2023

Comp Applic In Engineering

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“…This tool offers a dedicated DSL that can be used to define sets of mutation operators for any DSL defined by an Ecore metamodel. The tool helps in evaluating the coverage of such set for the language by providing coverage metrics of the operators w. r .t the metamodel [21]. Once the operator set is designed, the tool can systematically apply those operators on initial models, to create sets of mutants.…”

Section: Tool Supportmentioning

confidence: 99%

Automatic test amplification for executable models

Khorram

Bousse

Mottu

et al. 2022

Proceedings of the 25th International Conference on Model Driven Engineering Languages and Systems

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Behavioral models are important assets that must be thoroughly verified early in the design process. This can be achieved with manuallywritten test cases that embed carefully hand-picked domain-specific input data. However, such test cases may not always reach the desired level of quality, such as high coverage or being able to localize faults efficiently. Test amplification is an interesting emergent approach to improve a test suite by automatically generating new test cases out of existing manually-written ones. Yet, while ad-hoc test amplification solutions have been proposed for a few programming languages, no solution currently exists for amplifying the test cases of behavioral models.In this paper, we fill this gap with an automated and generic approach. Given an executable DSL, a conforming behavioral model, and an existing test suite, our approach generates new regression test cases in three steps: (i) generating new test inputs by applying a set of generic modifiers on the existing test inputs; (ii) running the model under test with new inputs and generating assertions from the execution traces; and (iii) selecting the new test cases that increase the mutation score. We provide tool support for the approach atop the Eclipse GEMOC Studio 1 and show its applicability in an empirical study. In the experiment, we applied the approach to 71 test suites written for models conforming to two different DSLs, and for 67 of the 71 cases, it successfully improved the mutation score between 3.17 % and 54.11 % depending on the initial setup. CCS CONCEPTS• Software and its engineering → Software testing and debugging; Model-driven software engineering.

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Systematic Engineering of Mutation Operators.

Cited by 2 publications

References 31 publications

Automated generation and correction of diagram‐based exercises for Moodle

Automated generation and correction of diagram‐based exercises for Moodle

Automatic test amplification for executable models

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