SOVA - A Tool for Semantic and Ontological Variability Analysis

Variability analysis in Software Product Line Engineering (SPLE) utilizes various software-related artifacts, including requirements specifications. Currently, measuring the similarity of requirements specifications for analyzing variability of software products mainly takes into account semantic considerations. This might lead to failure to capture important aspects of the software behavior as perceived by users. In this paper we present a tool, called SOVA – Semantic and Ontological Variability Analysis, which introduces ontological considerations to variability analysis, in addition to the semantic ones. The input of the tool is textual requirements statements organized in documents. Each document represents the expectations from or the characteristics of a different software product in a line, while each requirement statement represents an expected behavior of that software product. The output is a feature diagram representing the variability in the input set of requirements documents and setting the ground for behavioral domain analysis.

[1]  James Pustejovsky,et al.  Machine Learning of Temporal Relations , 2006, ACL.

[2]  M. Bunge.  Treatise on basic philosophy , 1974 .

[3]  Kyo Chul Kang,et al.  Feature-Oriented Domain Analysis (FODA) Feasibility Study , 1990 .

[4]  Carlo Strapparava,et al.  Corpus-based and Knowledge-based Measures of Text Semantic Similarity , 2006, AAAI.

[5]  Klaus Pohl,et al.  Software Product Line Engineering , 2005 .

[6]  Yair Wand,et al.  Analyzing Variability of Software Product Lines Using Semantic and Ontological Considerations , 2014, CAiSE.

[7]  Yair Wand,et al.  External Variability of Software: Classification and Ontological Foundations , 2011, ER.

[8]  Thomas Leich,et al.  FeatureIDE: A tool framework for feature-oriented software development , 2009, 2009 IEEE 31st International Conference on Software Engineering.

[9]  Heeyoung Lee,et al.  A Multi-Pass Sieve for Coreference Resolution , 2010, EMNLP.

[10]  Patrick F. Reidy.  An Introduction to Latent Semantic Analysis , 2009 .

[11]  Martha Palmer,et al.  Verb Semantics and Lexical Selection , 1994, ACL.

[12]  Nan Niu,et al.  Extracting and Modeling Product Line Functional Requirements , 2008, 2008 16th IEEE International Requirements Engineering Conference.

[13]  Mathieu Acher,et al.  Feature model extraction from large collections of informal product descriptions , 2013, ESEC/FSE 2013.

[14]  Ruzanna Chitchyan,et al.  A framework for constructing semantically composable feature models from natural language requirements , 2009, SPLC.

[15]  Paul Clements,et al.  Software product lines - practices and patterns , 2001, SEI series in software engineering.

[16]  Daniel Gildea,et al.  Automatic Labeling of Semantic Roles , 2000, ACL.

[17]  Peter W. Foltz,et al.  An introduction to latent semantic analysis , 1998 .

[18]  Yair Wand,et al.  Comparing functionality of software systems: An ontological approach , 2013, Data Knowl. Eng..

[19]  Jane Cleland-Huang,et al.  On-demand feature recommendations derived from mining public product descriptions , 2011, 2011 33rd International Conference on Software Engineering (ICSE).

[20]  Michel Jaring,et al.  Variability engineering as an integral part of the software product family development process , 2005 .