Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/477394
Title: | Fault pr Fault prone components identification and optimal test case generation using ocl specificationne components identification and optimal test case generation using ocl specification |
Researcher: | Jalila A |
Guide(s): | Chandrakumar T |
Keywords: | Software System Object Constraint Language Category Partitioning Method |
University: | Anna University |
Completed Date: | 2022 |
Abstract: | The most important quality aspect of a software system is how well it fulfills the needs of its users or the requirements of its customers. The demand for complicated software has been expanding at an exponential rate in recent years, as has the number of components in a system. However, due to a lack of time, a scarcity of allied resources and the high cost of the testing period, extensive testing on every component of the software is not achievable. In practice, a small number of system components might cause numerous problems to be reported at later stages of software development, leading to a huge loss of money, human effort, and quality for the system. Therefore, it is vital to devote a significant amount of time and effort to identifying and testing those components that are most prone to failure at the earliest. newlineSpecification-based testing is one of the most well-known software engineering principles. Apart from the application of formal specifications in precise and abstract system representation, this research effort has demonstrated additional benefits such as systematically prioritizing tests and automatically deriving test input data. To address this issue, the aim of this research is to examine the overlap between fault-prone component-based testing and specification-based testing, as well as the benefits that these two disciplines potentially provide. This can be achieved by initiating fault-proneness-based testing at the specification level so that errors can be identified and fixed early in the Software Development Life Cycle (SDLC). The reason behind is that errors discovered later in the software development life cycle cost more to correct than those discovered earlier. newlineThe primary goal of fault-proneness prediction is to identify fault-prone components as early as possible in the SDLC in order to reduce development effort in terms of design, coding, testing, inspection, and debugging, among other aspects. newline |
Pagination: | xix,153p. |
URI: | http://hdl.handle.net/10603/477394 |
Appears in Departments: | Faculty of Science and Humanities |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
01_title.pdf | Attached File | 96.66 kB | Adobe PDF | View/Open |
02_prelimpages.pdf | 784.53 kB | Adobe PDF | View/Open | |
03_contents.pdf | 326.84 kB | Adobe PDF | View/Open | |
04_abstracts.pdf | 157.86 kB | Adobe PDF | View/Open | |
05_chapter1.pdf | 369.86 kB | Adobe PDF | View/Open | |
06_chapter2.pdf | 218.42 kB | Adobe PDF | View/Open | |
07_chapter3.pdf | 929.69 kB | Adobe PDF | View/Open | |
08_chapter4.pdf | 511.33 kB | Adobe PDF | View/Open | |
09_chapter5.pdf | 753.8 kB | Adobe PDF | View/Open | |
10_chapter6.pdf | 783.34 kB | Adobe PDF | View/Open | |
11_annexures.pdf | 139.19 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 142.66 kB | Adobe PDF | View/Open |
Items in Shodhganga are licensed under Creative Commons Licence Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0).
Altmetric Badge: