Requirements Engineering is regarded as one of the most important functions in software development process. Inadequate/ incorrect engineering of requirements may lead to expensive errors in software development or even to project failure. Even though there are a different methods and approaches that are proposed in literatures, many of these approaches have not been used in the industry or have been proved to be ineffective. The main goal of this work is to investigate the Requirements Engineering weak points and see which of these weak points can be strengthened by the use of analytics.
In project, requirements definition is an important function that affects project processes and results. Dissatisfaction of the requirements may lead to unhappy customers, incorrect system processes or even project failure. The use of analytics allows to process the information that otherwise may be ignored or overlooked.
Based on Dick J., Hull E. & Jackson K. [3], Requirements Engineering (RE) is the subset of systems engineering concerned with discovering, developing, tracing, analysing, qualifying, communicating and managing requirements that define the system at successive levels of abstraction.
Dankov Y. and Birov D. [2] describes analytics as the process of developing actionable insights through problem definition and the application of statistical models and analysis against existing and/ or simulated future data.
The purpose of this paper is to reflect the results of the research in progress concerning the importance of the use of analytics in Requirements Engineering functions. Paper reports on three research questions: (i) “What is the state of art of the use of analytics?” (ii) “What are the Requirements Engineering challenges?” and (iii) “How the use of analytics in specified Requirements Engineering function can improve the weak point of Requirements Engineering?”.
The paper is structured as follows. The survey of the state of art of the use of analytics is presented in Section 2. Challenges in Requirements Engineering are presented in Section 3. Summary of Requirements Engineering challenges and the use of analytics to reduce the Requirements Engineering weak points are described in Section 4. Brief conclusions and directions of further research are stated in Section 5. 2
To understand the state of art of the use of analytics, a literature search was conducted using terms “use” and “analytics”. 25 sources where selected and analysed using Springer Link, Science Direct, IEEE resources, 13 of the sources, where identified as overlapping and are not included in a review. Collected sources of types of analytics are new and do not overlap with previous overview published in Pincuka and Kirikova article “Types of Analytics in Requirements Engineering” [16]. New overview was made to expand understanding of use of analytics in different fields.
The gathered articles, where analysed as follows: (i) “What is the industry in which analytics are used?”, (ii) “What kinds of analytics are used?” and (iii) “What the analytics is used for?”. Gathered kinds of analytics and their brief definition is described below: 1. 2. The collection of types of analytics and the industries in which they are used allows to (1) understand the main domains of application of analytics and (2) collect different methods and approaches how analytics can be applied in different fields, to understand how analytics can be applied in Requirements Engineering.
Gathered analytics are described without any classification into groups, because the purpose of this article is to understand use of analytics in different fields and if it is possible to apply this analytics in Requirements Engineering and overcome Requirements Engineering challenges. 3
Requirements Engineering deals with a lot of challenges, for example, authors Kahan et al. [9] mentions, previous identified requirements issues/ challenges like - business process focus, systems transparency, integration focus, distributed requirements, layers of requirements, packaged software, centrality of architecture, independent complexity and fluidity of design. Author Schmid [22] mentions Global Requirements Engineering challenges that are based on location of the stakeholders, in his article he mentions challenges with International Requirements Engineering and Distributed Requirements Engineering.
In this section Requirements Engineering challenges are collected based on Requirements Engineering phase in which challenge appears on.
Requirements Engineering function has a four phases [12]: • Elicitation is the act to determine or obtain the relevant requirements for the development of a solution. In this phase requirements are identified and discovered; • Requirements analysis is a phase, where a user’s requirements should be clarified, categorized and documented to generate the corresponding specification. • •
In this phase requirements classification, representation, derivation and negotiation are provided; Requirements specification describes the phase, where the requirements are brought into a suitable and unambiguous form. The idea in this phase is to document the requirements, and to make the requirements document readable and understandable to anyone; Requirements validation is to review or validation requirements for clarity, consistency and completeness. In this phase requirements faults are identified. Summarizing all of the challenges from different scientific papers (see Table 2.) the conclusion can be made, that often authors emphasizes the same challenges in the same phases of Requirements Engineering function. 4
Use of Analytics to Reduce Requirements Engineering Challenges In this Section using summarization of Requirements Engineering challenges are provided the types of analytics, which can be used to improve Requirements Engineering issues. In table 3 are mentioned only those Requirements Engineering challenges, to whom methods of analytics can be applied to, for example, analytics can not be used with challenges in customer/ client representatives or minimal documentation, in these cases other methods should be provided. Analytics, that can be applied to Requirements Engineering challenges where identified in a literature survey, based on analytics use cases and author master thesis Pincuka M. “Analytics in Requirements Engineering” [17]. Analytics, which are proposed to use in Requirements Engineering challenges are chosen based on use of analytics in a literature survey. Types of analytics that are provided in Table 3, only points out some of the analytics that can be used to improve or overcome Requirements Engineering challenges. For example, (i) business analytics can be used to understand the reality, if we will apply this analytics to Requirements Engineering it will help to better understand the requirement and it is meaning, (ii) if we identify conflicting requirements using descriptive analytics data can be classified and meaningful information about requirements can be found or (iii) using text analytics with keywords about the system we can identify some additional information to reduce lack of information. To summarize all methods of analytics that can be used to overcome Requirements Engineering challenges a literature study must be provided with focus on analytics and use cases, where methods of analytics are used.
In this paper Requirements Engineering challenges are discussed and the use of analytics to overcome these challenges envisioned. The paper contributes (i) a preliminary survey on the use of types of analytics in different industries, (ii) summary of Requirements Engineering challenges in Requirements Engineering phases and (iii) proposal to the use specific types of analytics to overcome identified Requirements Engineering challenges. Survey can be further researched collecting publications from different years, industries, main topics and use cases.
Use of analytics in Requirements Engineering has a big potential, but nowadays use of analytics in Requirements Engineering is still limited, the issues addressed in this work are rarely surveyed, structured and organized, so the knowledge of the use of analytics in Requirements Engineering could be reused and utilized effectively.
In previous research [16], first insights of use of analytics in Requirements Engineering were collected and this research is a step towards the effective utilization of different types of analytics in Requirements Engineering.
The presented research has several limitations – more sources of analytics and Requirements Engineering challenges can be identified, analytics can be grouped by the usage and use of analytics in Requirements Engineering challenges can be explained using examples.
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