As a part of computer science, software engineering is responsible for the in-depth study of the design, development, and technical support of software. It aims to meet the challenge of low-quality software development projects. With that said, measuring software reliability is regarded as a crucial concern for software engineers and policymakers. The level of reliability is essential since it indicates the progress of the system. Therefore, this report draws on the detailed analysis of software reliability measurement processes with a suggestion of a new groundwork of reliability measurement based on software metrics examined by Amar and Rabai.
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Defining the issue
To begin with, software measurement is an evolving area that facilitates the quality evaluation of software systems. Amar and Rabai (2017) state that, in terms of the variety of quality factors, reliability is one of the most important ones, which is also the “only common factor of different quality models”, such as McCall’s, Boehm’s, FURPS and ISO 25010 (p. 725). Hence, the measuring of reliability is the emphasis of the analyzed article, as it addresses various elements such as reliability techniques, models, and metrics concerning the software process.
Amar and Rabai (2017) define reliability as the external software quality factor, as the extent to which a specific system, product, or its element function within fixed conditions for a fixed period (p. 726). Besides, reliability indicator represents mathematical and statistical models, techniques, and metrics to analyze the issue in quantitive terms, as well as to foresee its level of reliability.
Software reliability process
The conference article discusses four significant phases of the basic reliability process that was previously proposed in 1996 and is based on the set of iterative activities. These phases include defining reliability objective (Phase 1), developing operational profile (Phase 2), model and measure reliability (Phase 3), and validating reliability in the field (Phase 4) (Amar and Rabai, 2017, p. 727). The phases are additionally examined and explained through the graphic chart. Thus, the first phase implies defining the objective based on existing products with a similar customer base, or by identifying setbacks and their intensity, the cost, and the delivery schedule.
The second phase, in turn, consists of four other steps, such as determination of customer’s profile, determination of the user’s profile, defining the system-mode profile, and determination of functional profile (Amar and Rabai, 2017, p. 727). The third phase deals with perform system testing, failure data gathering, as well as selection and usage of the applicable software reliability tools. Finally, the fourth phase comprises submitting the comments to strengthen the process and set the reliability’s growth.
The Suggested Reliability Measurement Framework
According to the presented issues, Amar and Rabai suggest the renewal to demonstrate the use of reliability techniques and metrics over different phases of the software development life cycle (SDLC). This includes two major phases: the implementation and testing phase, and reliability validation (Amar and Rabai, 2017, p. 729). The first phase implies using reliability models and sematic and syntactic metrics. This testing helps predict fault intensity and the level of reliability. The second phase ensures the accomplishing of the reliability objective. Such improvements result in higher levels of reliability with lower levels of cost and time.
Amar and Rabai analyzed the fundamental principles of reliability measurements within the soft engineering aspect, along with detailed graphics charts. The new suggested groundwork covers the key elements of reliability measurement and demonstrates its use in different phases of the software development life cycle. The following study and research aimed at emphasizing the issue of reliability in software engineering and focuses on the usage of the suggested processes in real life.
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Amara, D., & Rabai, L. (2017). Towards a new framework of software reliability measurement based on software metrics. In The 8th International Conference on Ambient Systems, Networks and Technologies (pp. 725–730). Tunis: Procedia Computer Science.