literature Review- Software Testing

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cevlnaxnc2

Computer Science

Description

Literature review. Based on papers, thesis, journals or any legitim academic source (APA references please)

1st part - Describing test cases based on ontologies (skos,etc) (600 words)
2nd part - Test case abstraction after execution (what is that and how could be done) – 600 words
3rd part - Test case reusability (concepts and attributes) – 900 words
4th part - Test case reuse models and frameworks (as many as possible) – 1400 words

need 1st part by 14th , rest can be provided by 20th.

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Explanation & Answer

I made edits to the paper and focused more on ontology-based testing. I hope this meets your expectations. Don't hesitate to reach out if you need anything edited.

Describing Test Cases Based on Ontologies
Test cases define the aligned conditions under which a software tester determines if a system
undergoing tests works correctly or meets the set requirements. As the process of testing is in
progress other problems can be identified this way to enhance the software’s requirements.
Test cases, also referred to as test scenarios allow the tester to place themselves in the user’s
shoes in order to identify realistic cases and thus use the scenarios of the application or software
undergoing tests (Jorgensen, 2016).
Case testing, which would otherwise be referred to scenario testing, is an alternative of software
testing, where real cases or scenarios are implemented during testing. Such cases play a crucial
role in providing an easier way testing complicated software, applications or systems. These
scenarios present, to software testers, methodologies and methods to come up with ontologies
(Ammann & Offutt, 2016).
Ontologies are formal models, representing the concepts within a domain as well as the
correlation of these concepts. The methods and methodologies are a representation of the
primitives which include information such as what they mean of their effect on the system under
testing. In database systems, ontology can be perceived as an amount of abstraction done for data
models, relational, of analogous to hierchial concepts. These concepts, however, are intended
only for modelling the attributes of individuals, their amount of knowledge as well as their
impact on other people (Bhatia et al., 2016). Typically, ontologies are made in particulate
languages which accommodate abstraction away from implementation frameworks and data
structures. Due to this, ontologies are said to be on a ‘sematic’ level while models of data such as
database schema are placed at the ‘physical’ or ‘logical level.’
Formalization of Ontology
Five elements formalize ontology. They are:







Instances: Are a representation of elements.
Function terms: These are complex structures derived from various relations which can
be replaced with individual terms in a statement.
Relations: These are ways which individuals and classes can have a relation to one
another. Formally, their definition is any subset of the product of n sets. R:C1 x C2x … x
Cn. Relations commonly used are part-of, attribute-of, instance of and kind-of
Classes: Include object types, concepts, collections, sets and classes in programming.
Axioms: These are model sentences that are always true (Guo et al., 2011).
SKOS

The SKOS (short for Simple Knowledge Organization System) is one of the Semantic Web
Standard, as SPARQL, RDF and OWL are. SKOS is a standard data model used to link and
share knowledge organization system through the inte...


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