TY - GEN
T1 - Change impact analysis for Natural Language requirements
T2 - 23rd IEEE International Requirements Engineering Conference, RE 2015
AU - Arora, Chetan
AU - Sabetzadeh, Mehrdad
AU - Goknil, Arda
AU - Briand, Lionel C.
AU - Zimmer, Frank
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/11/4
Y1 - 2015/11/4
N2 - Requirements are subject to frequent changes as a way to ensure that they reflect the current best understanding of a system, and to respond to factors such as new and evolving needs. Changing one requirement in a requirements specification may warrant further changes to the specification, so that the overall correctness and consistency of the specification can be maintained. A manual analysis of how a change to one requirement impacts other requirements is time-consuming and presents a challenge for large requirements specifications. We propose an approach based on Natural Language Processing (NLP) for analyzing the impact of change in Natural Language (NL) requirements. Our focus on NL requirements is motivated by the prevalent use of these requirements, particularly in industry. Our approach automatically detects and takes into account the phrasal structure of requirements statements. We argue about the importance of capturing the conditions under which change should propagate to enable more accurate change impact analysis. We propose a quantitative measure for calculating how likely a requirements statement is to be impacted by a change under given conditions. We conduct an evaluation of our approach by applying it to 14 change scenarios from two industrial case studies.
AB - Requirements are subject to frequent changes as a way to ensure that they reflect the current best understanding of a system, and to respond to factors such as new and evolving needs. Changing one requirement in a requirements specification may warrant further changes to the specification, so that the overall correctness and consistency of the specification can be maintained. A manual analysis of how a change to one requirement impacts other requirements is time-consuming and presents a challenge for large requirements specifications. We propose an approach based on Natural Language Processing (NLP) for analyzing the impact of change in Natural Language (NL) requirements. Our focus on NL requirements is motivated by the prevalent use of these requirements, particularly in industry. Our approach automatically detects and takes into account the phrasal structure of requirements statements. We argue about the importance of capturing the conditions under which change should propagate to enable more accurate change impact analysis. We propose a quantitative measure for calculating how likely a requirements statement is to be impacted by a change under given conditions. We conduct an evaluation of our approach by applying it to 14 change scenarios from two industrial case studies.
KW - Change Impact Analysis
KW - Natural Language Processing (NLP)
KW - Natural Language Requirements
UR - http://www.scopus.com/inward/record.url?scp=84962424897&partnerID=8YFLogxK
U2 - 10.1109/RE.2015.7320403
DO - 10.1109/RE.2015.7320403
M3 - Conference contribution
AN - SCOPUS:84962424897
T3 - 2015 IEEE 23rd International Requirements Engineering Conference, RE 2015 - Proceedings
SP - 6
EP - 15
BT - 2015 IEEE 23rd International Requirements Engineering Conference, RE 2015 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 24 August 2015 through 28 August 2015
ER -