SEKE 2012 Proceedings - Knowledge Systems Institute

Step 5: In this step, the user adapts the solutions of similar
cases, defined in step 4, for the new problem.
Step 6: Finally, the new case adapted is stored in the Case
Base.
IV. PROOF OF CONCEPT
Table 2 shows the experimental results of our approach
when two new real input problems were compared with a Case
Base containing 46 cases, occurring in software projects of a
company run by the federal government of Brazil. The retrieval
of cases by attribute-value similarity, processed by CBR
component, decreases the universe of cases to be processed by
the NLP component. For Case 1, we had a 29% decrease and
for Case 2, we had a 75% decrease. Furthermore, it was
possible to corroborate that the selection by similarity of the
descriptive texts of the problem is what, in fact, determines the
similar cases for reuse of solutions. Case 2 was, in fact, a new
case and refining process performed by the NLP component
correctly not selected any of the seven cases initially similar for
reuse. However, it is noteworthy that the initial search by
attributes, although not a determining factor, is important when
the Case Base is large. This experiment also allowed us to
identify a point of improvement in the NLP component: one of
the three cases selected for reuse in Case 1 was a false positive
case.
The parameters used in this experiment were: P Artifact = 1,
P Causer = 3 e P Cause = 5 (Step2); Cutoff value for measure Sim A
= 50% (Step 2); m = 2 (number of words in common) (Step 4).
Iterations of this experiment were carried out by randomly
varying the values of these parameters and, for the Case Base
in question, the aforementioned values were those that
presented the best results.
TABLE 2. RESULTS OF USAGE OF THE EXPERIENCE REUSE TOOL.
Case
1
2
Attributes
Artifact: Business Rule
Causer: Person
Cause: Wrong Business Rule
Specified
Description: Search
functionality specified in wrong
fields
Artifact: Vision Document
Causer: Technology
Cause:Vision Document
changed
Description: Changes in
functionality made it
impossible to use technology
previously chosen
Process
Component
CBR
Component
NLP
Component
CBR
Component
NLP
Component
Selected
Cases
33
3
7
0
V. CONCLUSION
This paper presents an ongoing approach to support the
reuse of experiences in RE. The distinguishing feature of the
approach is the use of AI techniques, specifically, Case Based
Reasoning and Natural Language Processing techniques. The
latter enables the representation of cases to take place in a more
natural and complete manner, that is, by describing the case in
natural language, whereby it is possible to make explicit the
essence and details of each case. We executed experiments that
corroborate our argument that the similarity by the textual
description of the cases is more determining than the attributevalue
similarity, making the process of reuse of solutions more
effective and useful. As an evolution of this proposal, we are
working on incorporating the semantic analysis of texts through
a common-sense conceptual base in the Portuguese and English
languages – InferenceNet [8], thus improving the accuracy of
the proposed approach.
REFERENCES
[1] Pereira, S. C. (2007) “Um estudo Empírico sobre Engenharia de
requisitos em Empresas de Produtos de Software”. Dissertação de
Mestrado em Ciências da Computação. Centro de Informática,
Universidade Federal de Pernambuco.
[2] Standish, Standish Group. (1994) The Chaos Report.
http://www.standishgroup.com/sample_research/chaos_1994_1.php
[3] Joshi, S.R., McMillan, W.W. (1996). Case Based Reasoning Approach
to Creating User Interface Components. Proceedings of the CHI '96
conference companion on Human factors in computing systems:
common ground
[4] Gabineski, R., Lorensi, F. (2007) Sistemas Multiagente Baseados em
Casos de Apoio á Gerência de Projetos. VIII Salão de iniciação
Científica e Trabalhos Acadêmicos.
[5] Jani, H. M., Mostafa, S. A. (2007) Implementing Case-Based Resorsing
Technique to Software Requirement Specifications Quality Analysis.
International Journal of Advancements in Computing Technology.
Volume 3, Number 1.
[6] Praehofer, H., Kerschbaummayr, J. (1999) Case-Based Resorsing
techniques to support reusability in a requirement engineering and
system desing tool. University Linz, departement os systems theory and
information technology. Institute of Systems Science. Austria.
[7] Wangehheim, C.G., Wangehheim, A. (2003) Raciocínio Baseado em
Casos. Editora Manole. 1º edição.
[8] Pinheiro, V., Pequeno, T., Furtado, V., Franco, W. (2010)
InferenceNet.Br: Expression of Inferentialist Semantic Content of the
Portuguese Language. In: T.A.S. Pardo et al. (eds.): PROPOR 2010,
LNAI 6001, pp.90-99. Springer, Heidelberg.
[9] Bick, E. The Parsing System “Palavras”. (2000) Automatic Grammatical
Analysis of Portuguese in a Constraint Grammar Framework. Aarhus
University Press. http://beta.visl.sdu.dk/visl/pt/index.php
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