Proceedings of the 38th International Conference on Software Engineering 2016
DOI: 10.1145/2884781.2884801
|View full text |Cite
|
Sign up to set email alerts
|

Probing for requirements knowledge to stimulate architectural thinking

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
7
0

Year Published

2016
2016
2020
2020

Publication Types

Select...
4
2

Relationship

1
5

Authors

Journals

citations
Cited by 16 publications
(7 citation statements)
references
References 29 publications
0
7
0
Order By: Relevance
“…"Probing for Requirements Knowledge to Stimulate Architectural Thinking," by Preethu Anish and her colleagues, describes an inexpensive, down-to-earth requirements elicitation technique to ensure that software requirement speci cations (SRSs) contain architecturally relevant information. 1 This research aims to equip business analysts with the appropriate probing questions (PQs) software architects typically ask. This will enable the analysts to elicit and specify architecturally relevant information themselves.…”
Section: Asking the Right Questionsmentioning
confidence: 99%
“…"Probing for Requirements Knowledge to Stimulate Architectural Thinking," by Preethu Anish and her colleagues, describes an inexpensive, down-to-earth requirements elicitation technique to ensure that software requirement speci cations (SRSs) contain architecturally relevant information. 1 This research aims to equip business analysts with the appropriate probing questions (PQs) software architects typically ask. This will enable the analysts to elicit and specify architecturally relevant information themselves.…”
Section: Asking the Right Questionsmentioning
confidence: 99%
“…Based on the analysis of the survey findings, PQ-flows for the 15 ASFR categories were created. This study is published in [35].…”
Section: Research Methodology At a Glancementioning
confidence: 99%
“…For automating this recommendation, we evaluated existing machine learning techniques on our dataset to find if it is feasible to automate the recommendation and annotation of PQ-flows. Initial results on this are reported in [35]. We note that design of machine learning techniques is out of scope for this research.…”
Section: Research Methodology At a Glancementioning
confidence: 99%
See 2 more Smart Citations