Auflistung nach Autor:in "Beer, Armin"
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- WorkshopbeitragComparison of the FMEA and STPA safety analysis methods-a case study(Software Engineering and Software Management 2019, 2019) Sulaman, Sardar Muhammad; Beer, Armin; Felderer, Michael; Höst, MartinThis summary refers to the paper ’Comparison of the FMEA and STPA safety analysis methods–a case study’ [Su17]. The paper was published as an article in the Software Quality Journal. It compares the Failure Mode and Effect Analysis (FMEA) and the System Theoretic Process Analysis (STPA) in an industrial case study.
- KonferenzbeitragDie Einführung eines wieder verwendbaren Testframeworks in der Sozialversicherung(Software Engineering 2008, 2008) Beer, Armin
- KonferenzbeitragFörderung der Nachhaltigkeit durch Modell-basiertes Testen(Softwaretechnik-Trends Band 43, Heft 3, 2023) Mohacsi, Stefan; Beer, Armin; Lorey, Tobias; Felderer, MichaelIn diesem Beitrag untersuchen wir die Frage, was Nachhaltigkeit in Bezug auf den SW-Test bedeutet und wie speziell Modell-basiertes Testen zur Verbesserung der Nachhaltigkeit beitragen kann. Ein einfaches Beispiel ist der Schutz der Umwelt durch die Berücksichtigung von Energieeffizienz beim Design der SW und der Testplanung. Ein solches Sustainability Engineering erfordert eine Paradigmen-Verschiebung bei einer Reihe von Faktoren wie Projektorganisation, Teamstruktur und Priorisierung der Qualitätsmerkmale. Auch umfasst Nachhaltigkeit nicht nur Umweltaspekte. Nur durch die frühzeitige Berücksichtigung von Nachhaltigkeits-Aspekten wie der Wartbarkeit war es möglich, dass die beim JWST im Betrieb aufgetretenen technischen Schwierigkeiten gemeistert werden konnten.
- ZeitschriftenartikelEine industriell erprobte Methode für Review und Test von Anforderungen mit Hilfe von Fehlertaxonomien(Softwaretechnik-Trends: Vol. 34, No. 1, 2014) Felderer, Michael; Beer, Armin
- ZeitschriftenartikelModel-based Testing and Verification of Dependable Systems(Softwaretechnik-Trends Band 29, Heft 3, 2009) Beer, ArminTesting of dependable event-based systems is very important to ensure that all requirements (including nonfunctional requirements such as reliability, availability, safety and security) are met, and the relevant standards are observed. In this paper we provide an overview of the state of the practice in testing dependable event-based systems and identify the challenges that have to be addressed in the future. We illustrate our findings by a case study for a transportation system. The most important topics for research and improvement are: (1) formal modeling techniques for domain experts, (2) smart monkey testing techniques for reliability testing (3) mutation analysis to reveal the defect-detection potential of test suites, and a (4) recommending tool for the selection of test-case design methods.
- KonferenzbeitragMutual knowledge transfer between industry and academia to improve testing withdefect taxonomies(Software-engineering and management 2015, 2015) Felderer, Michael; Beer, ArminSoftware engineering is an applied research area preferably conducted jointly by academia and industry to enable transfer of knowledge in both directions and at the end improvement software engineering in industry. In this paper we present how the required mutual knowledge transfer via empirical evaluation was performed to improve testing with defect taxonomies in industry.
- KonferenzbeitragRequirements-based testing with defect taxonomies(Software-engineering and management 2015, 2015) Felderer, Michael; Beer, ArminIn this paper we summarize requirements-based testing with defect taxonomies which seamlessly integrates defect taxonomies into the standard test process to improve the effectiveness and the efficiency of testing requirements. Defect taxonomies which consist of hierarchies of defect categories provide information about the distribution of faults and failures in a project. In practice, most defect taxonomies are only used for the a-posteriori allocation of testing resources to prioritize failures for debugging purposes. Requirements-based testing with defect taxonomies (RTDT), which has been defined and evaluated in several previous publications [FB12], [FB13a], [FB13b], [FB14a], [FB14c], [FBP14], exploits the full potential of defect taxonomies to control and improve all phases of the overall test process, i.e., test planning, design, execution and evaluation. Figure 1 summarizes the process steps and artifacts of RTDT. 2: Link and Validate Requirements and Defect Taxonomy Defect Taxonomy Requirements Specification Defect Category of Beizer DC Description of DC Severity 1: Create Defect $\cdots \cdots \cdots $REQ Description Priority Taxonomy $\cdots \cdots 15$ Data storage high 4xxx . Data D1 Incorrect access $\cdots $normal 27 Search function medium 42xx . . Data access . D2 Erroneous save of critical data critical 40 Documentation high $\cdots \cdots \cdots \cdots \cdots \cdots \cdots \cdots 3$: Plan Testing Test Strategy ID Test Design Test Strength 1 Test Strength 2 Test Strength 3 Technique (low) (normal) (high) TDS: Priority Severity Test Strength TDS1 Process cycle Main paths Branch coverage Loop coverage 6: Evaluate Sequence tests hi gh bl ocker, cri ti ca l , ma jor 3 oriented $\cdots \cdots \cdots \cdots \cdots $Tests norma l bl ocker, cri ti ca l $3 \cdots \cdots \cdots \cdots \cdots $TDD: norma l ma jor, norma l , mi nor, tri vi a l 2 Data TDD2 EP: Equivalence EP valid EP valid+invalid EP valid+invalid Partitioning l ow mi nor, tri vi a l