مقاله انگلیسی رایگان در مورد تکنیک های هوشمندانه Oncological برای تست نرم افزار هوشمند – 2019 IEEE

I- Introduction

II- Terminologies

III- Myths in Software Testing

IV- Types of Testing

V- Software Mutation

VI- Related Works

VII- Oncological Mutation

VIII- Proposed Framework

IX- Conclusion And Future Works

References

Abstract

Biologically inspired computing techniques are highly on demand due to the inter-connection of various specialized fields and their requirement of adaptable methods in solving software engineering problems. Mutation testing has acquired much importance in this scenario. The concept of mutation testing has originated from the bio immune system. This paper is a novel study on mutation testing that proposes a framework OSWM (oncological software mutation) from oncological tests performed in human pancreatic cancer cells. The framework connects the relationship between cancer cell tests and software tests ensuring mutation tests owe its origin from human cells tested. The study argues an intelligent software with an efficient immune system can therefore aim at testing, diagnosing and healing on its own.

INTRODUCTION

The significance of software testing is attributed in achieving and evaluating the excellence of software specifications as per the standard requirements. The essentiality of testing a software is huge so as to ensure you deliver the right product to the market.
Software tests can be conducted in different patterns. Typically this depends on the set of data you choose to test your software with. That is the data that can hold more probability of finding errors or that can have lesser probability of finding errors. Therefore any software product is expected to have undergone rigorous testing before it reaches the market especially if has to be dealing with human safety [1]. Thus the understanding of true software testing can make a profound difference in the success of a project [2].
The concept of unethical and dangerous laboratory experiments being eliminated using executable biological prediction software [3] has gained a lot of importance in the bio-inspired conceptual algorithms.
A system has an ability to be itself dependable in a persistent way even when there are failures in the system [4]. This concept is many a time matched with the fault tolerance system in a software to prove its resilience when matched with the bio-immune system.