Architecture for the Use of Synergies between Knowledge Engineering and Requirements Engineering

Sagrado, José del; Orellana, Francisco J.

doi:10.1007/978-3-642-25274-7_22

Cited by 5 publications

(8 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Some studies do not exclusively belong to RE, because they deal with several software engineering areas or topic, but did specifically include a reference to this development stage S1, S14 and S15. Additionally, we found studies that proposed general approaches for applying BNs in order to enhance the final results of the software development processes S14 and [17] in S2. Now, let us take a look at the second level of RE-related topics (see Table 2).…”

Section: Rq1: What Are the Re Knowledge Areas To Which Bns Have Been mentioning

confidence: 98%

“…Table 3 includes the indicators (i.e., metrics) for individual requirements that have been included as variables in the BNs. Figure 2 shows a BN for one of the datasets studied in [17]. The number of conditions (conditional) in a requirement has a direct influence on the number of actions and interfaces (sources) of that requirement.…”

Section: Bayesian Network and Requirements Engineeringmentioning

confidence: 99%

“…An example of BN application in an RE task is the work of del Sagrado & del Aguila [17]. This specifically focused on the identification and assessment of risky requirements.…”

Section: Bayesian Network and Requirements Engineeringmentioning

confidence: 99%

“…In order to assess the risk level of this requirement, the above information (evidence) is propagated through the BN in an inference process. The BN responds with a risk level of 2, which is the value obtaining the highest probability (i.e., 92.6 %), (see [17] for details).…”

Section: Bayesian Network and Requirements Engineeringmentioning

confidence: 99%

“…The application of any AI technique to this workflow must run a parallel path in order to facilitate the independent evolution of the AI technique itself and the RE stage [17] in S2. The advantages of using BNs in RE are their ability to reason under uncertainty along with the combination of a graphical representation based on sound mathematics (i.e., probability theory).…”

Section: Rq4: What Are the Advantages And Disadvantages Of Using Bns mentioning

confidence: 99%

See 4 more Smart Citations

Bayesian networks for enhancement of requirements engineering: a literature review

Cano

2015

Requirements Eng

Self Cite

View full text Add to dashboard Cite

Requirements analysis is the software engineering stage that is closest to the users' world. It also involves tasks that are knowledge intensive. Thus, the use of Bayesian networks (BNs) to model this knowledge would be a valuable aid. These probabilistic models could manage the imprecision and ambiguities usually present in requirements engineering (RE). In this work, we conduct a literature review focusing on where and how BNs are applied on subareas of RE in order to identify which gaps remain uncovered and which methods might engineers employ to incorporate this intelligent technique into their own requirements processes. The scarcity of identified studies (there are only 20) suggests that not all RE areas have been properly investigated in the literature. The evidence available for adopting BNs into RE is sufficiently mature yet the methods applied are not easily translatable to other topics. Nonetheless, there are enough studies supporting the applicability of synergistic cooperation between RE and BNs. This work provides a background for understanding the current state of research encompassing RE and BNs. Functional, non-functional and -ilities requirements artifacts are enhanced by the use of BNs. These models were obtained by interacting with experts or by learning from databases. The most common criticism from the point of view of BN experts is that the models lack validation, whereas requirements engineers point to the lack of a clear application method for BNs and the lack of tools for incorporating them as built-in help functions.

show abstract

Section: Rq1: What Are the Re Knowledge Areas To Which Bns Have Been mentioning

confidence: 98%

Section: Bayesian Network and Requirements Engineeringmentioning

confidence: 99%

“…An example of BN application in an RE task is the work of del Sagrado & del Aguila [17]. This specifically focused on the identification and assessment of risky requirements.…”

Section: Bayesian Network and Requirements Engineeringmentioning

confidence: 99%

Section: Bayesian Network and Requirements Engineeringmentioning

confidence: 99%

Section: Rq4: What Are the Advantages And Disadvantages Of Using Bns mentioning

confidence: 99%

See 3 more Smart Citations