scholarly journals Model-driven acceptance test automation based on use cases

2015 ◽  
Vol 12 (2) ◽  
pp. 707-728 ◽  
Author(s):  
Tomasz Straszak ◽  
Michał Śmiałek
Keyword(s):  
Specification Language ◽  
Acceptance Testing ◽  
Functional Domain ◽  
Test Cases ◽  
Acceptance Test ◽  
Test Automation ◽  
Model Driven ◽  
Use Case Models ◽  
Model Driven Approach ◽  
Requirements Models

Acceptance testing is highly dependent on the formulation of requirements, as the final system is tested against user requirements. It is thus highly desirable to be able to automate transition from requirements to acceptance tests. In this paper we present a model-driven approach to this issue, where detailed use case models are transformed into test cases. Importantly, our approach facilitates synchronising functional test cases with other types of tests (non-functional, domain logic, user interface) and introducing test data. This leads to a unified approach where requirements models of various kind drive the acceptance testing process. This process is parallel to the development process which also involves automatic transformations from requirements models to software development artefacts (models and code). To show validity of the approach we present a case study which uses a new tool called ReDSeT, that transforms requirements formulated in the Requirements Specification Language (RSL) into tests in a newly proposed Test Specification Language (TSL).

Cost and Effectiveness of Search-Based Techniques for Model-Based Testing: An Empirical Analysis

2017 ◽  
Vol 27 (04) ◽  
pp. 601-622 ◽  
Author(s):  
Aneesa Saeed ◽  
Siti Hafizah Ab Hamid ◽  
Asmiza Abdul Sani
Keyword(s):  
Test Data ◽  
Random Search ◽  
Test Cases ◽  
Optimal Test ◽  
Model Driven ◽  
Model Based ◽  
Model Based Testing ◽  
Generate Test Data ◽  
The Cost ◽  
Model Driven Approach

Model-based testing (MBT) seems to be gaining interest in industry and academia due to its provision of systematic, automated and comprehensive testing. The challenge in MBT is to generate optimal test data to execute test cases. Recently, researchers have successfully applied search-based techniques (SBTs) by automating the search for an optimal set of test data at reasonable cost compared to other more expensive techniques. In real complex systems, effectiveness and cost of SBTs for MBT in industrial context are little known. The objective of this study is to empirically evaluate the cost and the effectiveness of SBTs for MBT on industrial case studies. We applied a model-driven approach and SBTs to automatically generate executable feasible test cases. The results show that the model-driven approach generated high number of infeasible test cases with less time while genetic algorithm (GA) and simulating annealing (SA) outperformed significantly random search (RS) with high generation time. We concluded that local SBTs are more appropriate to generate test data when the type of the constraints is simple. Current work on analyzing the cost and effectiveness on SBTs for MBT indicates possible enhancement using the model-driven approach to detect the infeasible paths and SBTs to achieve optimal success rate.

scholarly journals Scheduling an aperiodic flow within a real-time system using Fairness properties

2014 ◽  
Vol Volume 18, 2014 ◽  
Author(s):  
Annie Choquet-Geniet ◽  
Sadouanouan MALO
Keyword(s):  
Real Time ◽  
Acceptance Test ◽  
Periodic Tasks ◽  
Real Time System ◽  
Model Driven ◽  
Aperiodic Tasks ◽  
International Audience ◽  
Hard Real Time ◽  
Model Driven Approach ◽  
Time Systems

International audience We consider hard real-time systems composed of periodic tasks and of an aperiodic flow. Each task, either periodic or aperiodic, has a firm deadline. An aperiodic task is accepted within the system only if it can be completed before its deadline, without causing temporal failures for the periodic tasks or for the previously accepted aperiodic tasks. We propose an acceptance test, linear in the number of pending accepted aperiodic tasks. This protocol can be used provided the idle slots left by the periodic tasks are fairly distributed. We then propose a model-driven approach, based on Petri nets, to produce schedules with a fair distribution of the idle slots for systems of non independent periodic tasks. Nous considérons des systèmes temps-réel composés de tâches périodiques et d’un fluxapériodique. Toutes les tâches, périodiques comme apériodiques, sont soumises à des échéancesstrictes. Une tâche apériodique n’est acceptée que si elle ne remet pas en cause le respect deséchéances par les tâches périodiques et par les tâches apériodiques déjà acceptées. Nous proposonsun protocole d’acceptation des tâches apériodiques de complexité linéaire en le nombre de tâchesapériodiques acceptées présentes dans le système. Ce protocle est utilisable dès lors que les tempscreux sont répartis de manière équitable. Nous proposons donc une approche modèle, à base deréseaux de Petri, pour produire des séquences où les temps creux sont équitablement répartis, pourdes systèmes de tâches interdépendantes.

Optimization of Favourable Test Path Sequences Using Bio-Inspired Natural River System Algorithm

2021 ◽  
Vol 14 (2) ◽  
pp. 85-105
Author(s):  
Nisha Rathee ◽  
Rajender Singh Chhillar
Keyword(s):  
Heuristic Algorithms ◽  
River System ◽  
Design Stage ◽  
Test Cases ◽  
Sequence Diagrams ◽  
Model Driven ◽  
Development Life Cycle ◽  
Software Development Life Cycle ◽  
Uml Activity Diagrams ◽  
Model Driven Approach

Testing of software requires a great amount of time and effort. The tester's main aim is to design optimized test sequences with a minimum amount of time, effort, and with less redundancy. Testers have used artificial intelligence meta-heuristic algorithms for optimization of test sequences. The model-driven approach is helpful in the generation of test sequences at early designing phase only. The model-driven approach uses UML diagram to represent the system's behavior and design test cases for the system at design stage of software development life cycle. The proposed approach uses natural river system for optimizing favourable non-redundant test path sequences using UML activity diagrams and sequence diagrams. The implementation of proposed approach has been done using python and results show that the proposed approach provides full coverage of test paths with less redundant test nodes compared to other meta heuristic algorithms.

A model-driven approach to cross-platform development of accessible business apps

2020 ◽  
Author(s):  
Christoph Rieger ◽  
Daniel Lucrédio ◽  
Renata Pontin M. Fortes ◽  
Herbert Kuchen ◽  
Felipe Dias ◽  
...  
Keyword(s):  
Model Driven ◽  
Cross Platform ◽  
Platform Development ◽  
Model Driven Approach

scholarly journals Learn-CIAM: A Model-Driven Approach for the Development of Collaborative Learning Tools

2021 ◽  
Vol 11 (6) ◽  
pp. 2554
Author(s):  
Yoel Arroyo ◽  
Ana I. Molina ◽  
Miguel A. Redondo ◽  
Jesús Gallardo
Keyword(s):  
Collaborative Learning ◽  
Methodological Approach ◽  
Automatic Generation ◽  
Learning Activities ◽  
Learning Tools ◽  
Model Driven ◽  
Collaborative Tools ◽  
Learning Tasks ◽  
Collaborative Learning Tools ◽  
Model Driven Approach

This paper introduces Learn-CIAM, a new model-based methodological approach for the design of flows and for the semi-automatic generation of tools in order to support collaborative learning tasks. The main objective of this work is to help professors by establishing a series of steps for the specification of their learning courses and the obtaining of collaborative tools to support certain learning activities (in particular, for in-group editing, searching and modeling). This paper presents a complete methodological framework, how it is supported conceptually and technologically, and an application example. So to guarantee the validity of the proposal, we also present some validation processes with potential designers and users from different profiles such as Education and Computer Science. The results seem to demonstrate a positive reception and acceptance, concluding that its application would facilitate the design of learning courses and the generation of collaborative learning tools for professionals of both profiles.

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