Abstract
In market-driven software development there is a strong
need for support to handle congestion in the requirements
engineering process, which may occur as the
demand for short time-to-market is combined with a
rapid arrival of new requirements from many different
sources. Automated analysis of the continuous flow of
incoming requirements provides an opportunity to
increase the efficiency of the requirements engineering
process. This paper presents empirical evaluations of the
benefit of automated similarity analysis of textual
requirements, where existing information retrieval
techniques are used to statistically measure requirements
similarity. The results show that automated
analysis of similarity among textual requirements is a
promising technique that may provide effective support
in identifying relationships between requirements.
need for support to handle congestion in the requirements
engineering process, which may occur as the
demand for short time-to-market is combined with a
rapid arrival of new requirements from many different
sources. Automated analysis of the continuous flow of
incoming requirements provides an opportunity to
increase the efficiency of the requirements engineering
process. This paper presents empirical evaluations of the
benefit of automated similarity analysis of textual
requirements, where existing information retrieval
techniques are used to statistically measure requirements
similarity. The results show that automated
analysis of similarity among textual requirements is a
promising technique that may provide effective support
in identifying relationships between requirements.
| Original language | English |
|---|---|
| Pages (from-to) | 20-33 |
| Journal | Requirements Engineering |
| Volume | 7 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 2002 |
Subject classification (UKÄ)
- Computer Science