Contributo in atti di convegno, 2012, ENG, 10.1145/2245276.2231939

A clustering-based approach for discovering flaws in requirements specifications

Ferrari A., Gnesi S., Tolomei G.

CNR-ISTI, Pisa, Italy; CNR-ISTI, Pisa, Italy; DAIS, Università Ca' Foscari, Venezia, Italy;

In this paper, we present the application of a clustering algorithm to exploit lexical and syntactic relationships occurring between natural language requirements. Our experiments conducted on a real-world data set highlight a correlation between clustering outliers, i.e., requirements that are marked as "noisy" by the clustering algorithm, and requirements presenting "flaws". Those flaws may refer to an incomplete explanation of the behavioral aspects, which the requirement is supposed to provide. Furthermore, flaws may also be caused by the usage of inconsistent terminology in the requirement specification. We evaluate the ability of our proposed algorithm to effectively discover such kind of flawed requirements. Evaluation is performed by measuring the accuracy of the algorithm in detecting a set of flaws in our testing data set, which have been previously manually-identified by a human assessor.

27th Annual ACM Symposium on Applied Computing, pp. 1043–1050, Riva del Garda, Trento, ITALY, 26-30 marzo 2012

Keywords

Flawed requirements discovery, Requirement clustering, Requirements engineering

CNR authors

Gnesi Stefania, Ferrari Alessio

CNR institutes

ISTI – Istituto di scienza e tecnologie dell'informazione "Alessandro Faedo"

ID: 220743

Year: 2012

Type: Contributo in atti di convegno

Creation: 2013-05-31 09:58:42.000

Last update: 2023-03-08 13:35:23.000

External IDs

CNR OAI-PMH: oai:it.cnr:prodotti:220743

DOI: 10.1145/2245276.2231939

Scopus: 2-s2.0-84863576087

PUMA: cnr.isti/2012-A2-049