Exploiting model morphology for event-based testing
Başlık çevirisi mevcut değil.
- Tez No: 401248
- Danışmanlar: PROF. DR. FEVZİ BELLİ, PROF. DR. REINER DUMKE
- Tez Türü: Doktora
- Konular: Elektrik ve Elektronik Mühendisliği, Electrical and Electronics Engineering
- Anahtar Kelimeler: Belirtilmemiş.
- Yıl: 2014
- Dil: İngilizce
- Üniversite: Universität Paderborn
- Enstitü: Yurtdışı Enstitü
- Ana Bilim Dalı: Belirtilmemiş.
- Bilim Dalı: Belirtilmemiş.
- Sayfa Sayısı: 242
Özet
Özet yok.
Özet (Çeviri)
Testing is the process of checking a system under consideration whether it behaves as intended by the user. Model-based testing employs models for generation of test cases. Model-based mutation testing (MBMT) additionally involves fault models, called mutants, which are generated from the original model by applying mutation operators. A problem encountered in MBMT is caused by mutants that are equivalent to the original model (equivalent mutants) and multiple mutants that model the same faults. These mutants should be eliminated, because they lead to unnecessary test cases and thus increase the costs. Another problem of MBMT is the need to compare a mutant to the original model for test generation. Furthermore, using a single fixed model out of a set of various structurally, that is, morphologically, different models that describe a given system can also be considered as a problem of MBMT. This work proposes an event-based approach to MBMT that is not fixed on single events and a single model but rather operates on sequences of events of length k≥1 and invokes a sequence of models that are derived from the original one by varying its morphology based on the sequence length k. The approach employs formal grammars, introduces related mutation operators, and constructs algorithms, which enable the following and thus avoid the aforementioned drawbacks of MBMT: (1) the exclusion of mutants that are equivalent to the original model and multiple mutants that model the same faults; (2) the generation of a test case in linear time to kill a selected mutant without the necessity of comparing it to the original model; (3) the analysis of morphologically different models enabling the systematic generation of mutants, thereby extending the set of fault models under consideration or studied in related literature. Three case studies validate the approach, analyze its characteristics and compare it to two other MBMT approaches and random testing. A discussion about the adaptation of the proposed MBMT approach using various models, its weaknesses and limitations, and further research potential in the field concludes the work.
Benzer Tezler
- Building of Turkish propbank and semantic role labeling of Turkish
Türkçe önerme veri tabanının oluşturulması ve Türkçenin anlamsal görev çözümlemesi
GÖZDE GÜL ŞAHİN
Doktora
İngilizce
2018
Bilgisayar Mühendisliği Bilimleri-Bilgisayar ve Kontrolİstanbul Teknik ÜniversitesiBilgisayar Mühendisliği Ana Bilim Dalı
PROF. DR. EŞREF ADALI
- Towards a model for analyzing the cognitive gap in user-product interaction throughout the technological evolution
Kullanıcı-ürün etkileşiminde bilişsel boşluk: Teknolojik evrim açısından bir analiz modeli
BEYZA DOĞAN
Doktora
İngilizce
2024
Endüstri Ürünleri Tasarımıİstanbul Teknik ÜniversitesiEndüstriyel Tasarım Ana Bilim Dalı
PROF. DR. HATİCE HÜMANUR BAĞLI
- Ozon yağı nanopartiküllerinin kanser tedavisinde ın vıtro radyoduyarlılık potansiyellerinin araştırılması
Investigation of in vitro radiosensitivity potential of ozonated oil nanoparticles for cancer treatment
YELİZ YALÇIN
Doktora
Türkçe
2021
Radyasyon OnkolojisiZonguldak Bülent Ecevit ÜniversitesiNanoteknoloji Mühendisliği Ana Bilim Dalı
PROF. DR. RAHİME SEDA TIĞLI AYDIN
- Zamansallık ve mekansallık bağlamında heterotopyaların sentaktik ve semantik irdelenmesi
A syntactic and semantic research on the temporality and spatiality of heterotopias
İLGİ HACIHASANOĞLU
- Evrişimli sinir ağları kullanılarak retina görüntülerinin segmentasyonu ve sınıflandırılması
Segmentation and classification of retina images using convolutional neural networks
MALI MOHAMMEDHASAN
Doktora
Türkçe
2021
Bilgisayar Mühendisliği Bilimleri-Bilgisayar ve KontrolSelçuk ÜniversitesiBilgisayar Mühendisliği Ana Bilim Dalı
PROF. DR. HARUN UĞUZ