Abstract

Requirements Prioritization is an activity, part of Requirements Engineering, whose purpose is to determine the relevance that each requirement has within a software system to be developed. In order to conduct this activity, several requirements prioritization techniques have been proposed. However, companies and software developers do not know which techniques can give the best results possible or when to apply them. Choosing the wrong technique might lead the prioritization process to an inappropriate approach. This systematic literature review aims to know the state of the art of the prioritization techniques which have been used in software projects developed during the last decade, as well as knowing the benefits provided by their implementation. Our results show that AHP, Cumulative Voting, Cost-Value Approach, and Numerical Assignment were the most documented techniques. According to the studies reviewed, these techniques have specific advantages, for example, accuracy and effort reduction benefits. They also have disadvantages such as scalability issues and time consumption problems. However, the use of Requirements Prioritization Techniques, in general terms, generate cost and effort benefits as well as a considerable reduction in the time needed to conduct the Prioritization Process.

Keywords:
Requirement prioritization Computer science Prioritization Risk analysis (engineering) Scalability Requirements engineering Process (computing) Software Software requirements Relevance (law) Reliability engineering Software development Requirements management Engineering Management science Component-based software engineering Database

Metrics

15
Cited By
2.26
FWCI (Field Weighted Citation Impact)
50
Refs
0.91
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Software Engineering Techniques and Practices
Physical Sciences →  Computer Science →  Information Systems
Software Engineering Research
Physical Sciences →  Computer Science →  Information Systems
Software Reliability and Analysis Research
Physical Sciences →  Computer Science →  Software
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