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AST 2021
Fri 28 - Sat 29 May 2021
co-located with ICSE 2021
Fri 21 May 2021 17:15 - 17:45 at AST Room - Industrial case studies & Doctoral Students Chair(s): Breno Miranda

The software of elevators requires maintenance over several years to deal with new functionality, correction of bugs or legislation changes. To automatically validate this software, test oracles are necessary. A typical approach in industry is to use regression oracles. These oracles have to execute the test input both, in the software version under test and in a previous software version. This practice has several issues when using simulation to test elevators dispatching algorithms at system level. These issues include a long test execution time and the impossibility of re-using test oracles both at different test levels and in operation. To deal with these issues, we propose DARIO, a test oracle that relies on regression learning algorithms to predict the Qualify of Service of the system. The regression learning algorithms of this oracle are trained by using data from previously tested versions. An empirical evaluation with an industrial case study demonstrates the feasibility of using our approach in practice. A total of five regression learning algorithms were validated, showing that the regression tree algorithm performed best. For the regression tree algorithm, the accuracy when predicting verdicts by DARIO ranged between 79 to 87%.

Fri 21 May

Displayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change

16:30 - 18:15
Industrial case studies & Doctoral StudentsAST 2021 at AST Room
Chair(s): Breno Miranda Federal University of Pernambuco
16:30
15m
Short-paper
Continuous Testing Improvement Model
AST 2021
Maximiliano Agustin Mascheroni Universidad Nacional de La Plata, Emanuel Agustin Irrazábal Universidad Nacional del Nordeste, Gustavo Rossi Universidad Nacional de La Plata, LIFIA-Fac. Informatica, La Plata, Argentina
Pre-print Media Attached
16:45
30m
Long-paper
Model-based Automation of Test Scripts Generation Across Product Variants: a Railway Perspective
AST 2021
Alessio Bucaioni Mälardalen University, Fabio Di Silvestro Bombardier Railway Transportation, Inderjeet Singh Bombardier Railway Transportation, Mehrdad Saadatmand RISE Research Institutes of Sweden, Henry Muccini University of L'Aquila, Italy, Thorvaldur Jochumsson Bombardier Railway Transportation
Pre-print Media Attached
17:15
30m
Long-paper
Using Machine Learning to Build Test Oracles: an Industrial Case Study on Elevators Dispatching Algorithms
AST 2021
Aitor Arrieta University of Mondragon, Jon Ayerdi Mondragon Unibertsitatea, Miren Illarramendi Mondragon University, Aitor Agirre IKERLAN-IK4, Goiuria Sagardui University of Mondragon , Maite Arratibel Orona
Pre-print Media Attached
17:45
30m
Long-paper
Automatically Assessing and Extending Code Coverage for NPM Packages
AST 2021
Haiyang Sun Università della Svizzera italiana, Andrea Rosà University of Lugano, Switzerland, Daniele Bonetta Oracle Labs, Walter Binder University of Lugano, Switzerland
Media Attached

Information for Participants
Fri 21 May 2021 16:30 - 18:15 at AST Room - Industrial case studies & Doctoral Students Chair(s): Breno Miranda
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