Failure Prediction Approach in Agile Software Development

Failure Prediction Approach in Agile Software Development

Bulqees Alajaleen, Aysh Alhroob
Copyright: © 2022 |Pages: 11
DOI: 10.4018/IJSI.292025
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Abstract

Software failure prediction is an important activity during agile software development as it can help managers to identify the failure modules. Thus, it can reduce the test time, cost and assign testing resources efficiently. RapidMiner Studio9.4 has been used to perform all the required steps from preparing the primary data to visualizing the results and evaluating the outputs, as well as verifying and improving them in a unified environment. Two datasets are used in this work, the results for the first one indicate that the percentage of failure to predict the time used in the test is for all 181 rows, for all test times recorded, is 3% for Mean time between failures (MTBF). Whereas, SVM achieved a 97% success in predicting compared to previous work whose results indicated that the use of Administrative Delay Time (ADT) achieved a statistically significant overall success rate of 93.5%. At the same time, the second dataset result indicates that the percentage of failure to predict the time used is 1.5% for MTBF, SVM achieved 98.5% prediction.
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Programming testing has generally been separated into approval and check (V&V) (Alhroob A. , Alzyadat, Imam, & Jaradat, 2020). Approval is the way toward guaranteeing that the product coordinates the prerequisites, and check guarantees that the framework meets the useful determination building one of the most well-known definitions of approval is building the right frame, and checking is building the right frame. Programming building is loaded with vulnerability: A significant wellspring of issues during programming advancement is a vulnerability about necessities; a significant wellspring of issues during programming development is a vulnerability about plan and execution choices made during improvement (Barstow, 1988). Programming is one significant job which is driving the numerous electronic and business items. The advancement of these items makes an expansion in the requirement for the product. Testing is one important period of a product improvement life cycle.Scanning errors are performed in programming tools. Reliability is an important aspect of distinguishing characterizes quality. Programming unwavering quality models are numerical models that portray the sensible marvel of programming testing during the product improvement life cycle (Rafi, 2012).

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