Requirement Elicitation and its Automated Tools

1. ABSTRACT

With the rise in technology touching sky high like no one has ever seen this height. Starting from simples automation like a toy car to the highest of AI operated flights and Automated car, everything has started automating. The fast-growing software industry is never an exception. People started hiring people to automate things so that in the later time the hired person will no longer be needed. In a software Industry, everything starts from gathering the requirements which is called Requirement Elicitation. Requirement Elicitation is the most critical part because gathering the wrong requirement and producing the wrong end product directly results in the failure of the product. This Requirement Elicitation or Requirement Gathering is a time exhausting and error-prone when performed by requirement analysts. So that leads to a lot of research to automate the process. This paper aims to figure out the usage of which  automation tool is most widely used in requirement Elicitation Process through relating works and finding the effectiveness of the same .A small survey which was done with the help of limited crowd as a part of the Pilot study later discussed in this paper. The result from the survey helps to identify the effect of this Automation in the requirement Elicitation Process.

Keywords: Requirement Elicitation, Requirement Engineering, Automation, Effects of Automation.

2. INTRODUCTION

Requirement Engineering is the key stack of any software industry to cultivate and understand what the end-user, Client require to give the project the right direction. The key step in requirement Engineering include gathering, creating articles and verifying the Software Requirement Specifications (SRS). The Requirement Elicitation stands as the prime most step in Requirement Engineering because the wrong gathering of the requirement will absolutely end in the wrong end product. It is an accepted fact that if errors produced in requirement elicitation, if goes undetected till the very end turns out to be a costly mistake[1][2]. The key Stakeholders in this process includes the end-user, customers, product environment, system of implementation. It has been found that it turns out to be very difficult to motivate the customers what they want or even if the customer knows what he wants he might be hesitant to explain because of various reasons like lesser knowledge in the domain, Business politics, not clearly understanding what the end-user needs [3].So this had made the job of requirement analyst , software engineers very tough and requires them to shoot very selective question so as to reduce the aftermath effects.

Mich et al .states that the requirement gathering happens mostly through the medium of natural language[4].At the end of requirement elicitation all the documents in natural language will be formulated into more useful reports and documents which will be helpful in taking forward the project. Even though the natural language is the most prevailing medium in cultivating the requirements , they tend to cause intense problems when using it in specification documents as they might be unclear and uncertain [5].In large scale industry, it has become more challenging as a large number of natural language documents are gathered and has to be analysed. In this state manual requirement analysis turns out to be costly , time-consuming, error-prone[6]. So the above resulting in automating the process of requirement elicitation to a semi and full automated state.

The work presented in this paper is done with an aim to meet two research question .

RQ1:What percentage of companies uses Automation in Requirement Elicitation process?

RQ2: Which category of automation tool is widely used in the  process of requirement elicitation ?

RQ3:How effectively the tools were successful in getting to the best possible desired outcome which is the lesser error in the end product?

In the remainder of this paper, part 3 discusses on the State of the Art, part 4 describe the intended design of the study , part 5 describes the Pilot Study done with results and part 6 explains the conclusions. 

3. STATE OF THE ART