Test case selection (TCS) and test case prioritization (TCP) techniques can reduce time to detect the first test failure. Although these techniques have been extensively studied in combination and isolation, they have not been compared one against the other. In this paper, we perform an empirical study directly comparing TCS and TCP approaches, represented by the tools Ekstazi and FAST, respectively. Furthermore, we develop the first combination, named Fastazi, of file-based TCS and similarity-based TCP and evaluate its benefit and cost against each individual technique. We performed our experiments using 12 Java-based open-source projects. Our results show that, in the median case, the combined approach detects the first failure nearly two times faster than either Ekstazi alone (with random test ordering) or FAST alone (without TCS). Statistical analysis shows that the effectiveness of Fastazi is higher than that of Ekstazi, which in turn is higher than that of FAST. On the other hand, FAST adds the least overhead to testing time, while the difference between the additional time needed by Ekstazi and Fastazi is negligible. Fastazi can also improve failure detection in scenarios where the time available for testing is restricted. CCS CONCEPTS o Software and its engineering ->Software testing and debugging.

Comparing and combining file-based selection and similarity-based prioritization towards regression test orchestration

Bertolino A
2022

Abstract

Test case selection (TCS) and test case prioritization (TCP) techniques can reduce time to detect the first test failure. Although these techniques have been extensively studied in combination and isolation, they have not been compared one against the other. In this paper, we perform an empirical study directly comparing TCS and TCP approaches, represented by the tools Ekstazi and FAST, respectively. Furthermore, we develop the first combination, named Fastazi, of file-based TCS and similarity-based TCP and evaluate its benefit and cost against each individual technique. We performed our experiments using 12 Java-based open-source projects. Our results show that, in the median case, the combined approach detects the first failure nearly two times faster than either Ekstazi alone (with random test ordering) or FAST alone (without TCS). Statistical analysis shows that the effectiveness of Fastazi is higher than that of Ekstazi, which in turn is higher than that of FAST. On the other hand, FAST adds the least overhead to testing time, while the difference between the additional time needed by Ekstazi and Fastazi is negligible. Fastazi can also improve failure detection in scenarios where the time available for testing is restricted. CCS CONCEPTS o Software and its engineering ->Software testing and debugging.
2022
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
978-1-4503-9286-0
Regression testing
Test case selection
Test case prioritization
Test orchestration
Fastazi
File in questo prodotto:
File Dimensione Formato  
prod_469185-doc_189922.pdf

Open Access dal 17/06/2024

Descrizione: Postprint - Comparing and combining file-based selection and similarity-based prioritization towards regression test orchestration
Tipologia: Documento in Post-print
Licenza: Nessuna licenza dichiarata (non attribuibile a prodotti successivi al 2023)
Dimensione 410.92 kB
Formato Adobe PDF
410.92 kB Adobe PDF Visualizza/Apri
prod_469185-doc_189955.pdf

solo utenti autorizzati

Descrizione: Comparing and combining file-based selection and similarity-based prioritization towards regression test orchestration
Tipologia: Versione Editoriale (PDF)
Licenza: NON PUBBLICO - Accesso privato/ristretto
Dimensione 302.09 kB
Formato Adobe PDF
302.09 kB Adobe PDF   Visualizza/Apri   Richiedi una copia
prod_469185-doc_189975.pdf

accesso aperto

Descrizione: Preprint - Comparing and combining file-based selection and similarity-based prioritization towards regression test orchestration
Tipologia: Documento in Pre-print
Licenza: Nessuna licenza dichiarata (non attribuibile a prodotti successivi al 2023)
Dimensione 443.06 kB
Formato Adobe PDF
443.06 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/419233
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 8
  • ???jsp.display-item.citation.isi??? 5
social impact