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New Software Testing Strategy (PhD Thesis)

By: Material type: TextTextLanguage: English Publication details: Karachi : NED University of Engineering and Technology Department of Computer Science and Information Technology, 2009Description: IX, 246 p. : illSubject(s): DDC classification:
  • 005.14378242 BAI
Summary: Abstract : The research undertaken presents three new and improved software testing strategies which could be applied to any type of organizational information systems. It is expected that it will provide considerable assistance to the system testers/ developers. The three proposed testing strategies are as under: • Metric Space Based Software Testing Strategy (MSSTS). • Hypothetical Database Testing Strategy (HDTS). • Quantum Computing Based Software Testing Strategy (QCSTS). The first testing strategy is based on Metric Space, a well known mathematical topic from "Functional Analysis". We have developed formal notation "Formal Notation for Requirements Specification (FRS), a test environment (Test-bed), and a set of algorithms/tools". The testing strategy will provide immense confidence / assistance to software testers and system developers and can be conveniently applied to both scientific function as well as organizational systems. The second testing strategy is based on Hypothetical database, a quite new concept in the field of software testing. Using the knowledge of the concepts of Independent Update views (IUVs) and differential table (DT) we have created a new Hypothetical database state (HS). The proposed testing strategy shall conveniently and formally test the test suites requirements consisting of Insert, Delete, and Modify. The advantage of this approach (i.e. HDTS) is that the originality of the database remains intact throughout the experiments. Another benefit is that it is helpful for most business applications as well as other similar application. The third proposed testing strategy is based on Quantum Computing, another new concept in the field of software testing. In this strategy we used a well known quantum algorithm called, "Grover's Algorithm" to reduce the time complexity. The advantage of the said algorithm is that it facilitates in reducing the time complexity to great extent (i.e. by a factor of ON").
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Abstract :

The research undertaken presents three new and improved software testing strategies which could be applied to any type of organizational information systems. It is expected that it will provide considerable assistance to the system testers/ developers.

The three proposed testing strategies are as under:

• Metric Space Based Software Testing Strategy (MSSTS).
• Hypothetical Database Testing Strategy (HDTS).
• Quantum Computing Based Software Testing Strategy (QCSTS).

The first testing strategy is based on Metric Space, a well known mathematical topic from "Functional Analysis". We have developed formal notation "Formal Notation for Requirements Specification (FRS), a test environment (Test-bed), and a set of algorithms/tools".

The testing strategy will provide immense confidence / assistance to software testers and system developers and can be conveniently applied to both scientific function as well as organizational systems.

The second testing strategy is based on Hypothetical database, a quite new concept in the field of software testing. Using the knowledge of the concepts of Independent Update views (IUVs) and differential table (DT) we have created a new Hypothetical database state (HS).

The proposed testing strategy shall conveniently and formally test the test suites requirements consisting of Insert, Delete, and Modify. The advantage of this approach (i.e. HDTS) is that the originality of the database remains intact throughout the experiments. Another benefit is that it is helpful for most business applications as well as other similar application.

The third proposed testing strategy is based on Quantum Computing, another new concept in the field of software testing. In this strategy we used a well known quantum algorithm called, "Grover's Algorithm" to reduce the time complexity. The advantage of the said algorithm is that it facilitates in reducing the time complexity to great extent (i.e. by a factor of ON").