=Paper=
{{Paper
|id=Vol-1829/iStar17_paper_10
|storemode=property
|title=Recent Studies on i*: A Survey
|pdfUrl=https://ceur-ws.org/Vol-1829/iStar17_paper_10.pdf
|volume=Vol-1829
|authors=Affan Yasin,Lin Liu
|dblpUrl=https://dblp.org/rec/conf/istar/YasinL17
}}
==Recent Studies on i*: A Survey==
https://ceur-ws.org/Vol-1829/iStar17_paper_10.pdf
Recent Studies on i* : A Survey
Affan Yasin and Lin Liu
School of Software, Tsinghua University, Beijing, China
yayf15@mails.tsinghua.edu.cn
linliu@tsinghua.edu.cn
Abstract. i* is studied extensively in the requirements engineering and
information systems engineering literature since the 90s. The language
itself is gradually evolving and extended to iStar 2.0, and peoples in-
terest of study is also evolving in the meantime. In this paper, we sur-
veyed recent papers in a few major research databases, identifying key
research issues people are aiming at while study i* language. We clas-
sified the work according to the content and nature of the studies, such
as, modelling language, techniques, modelling applications, and teaching.
This helps us understand the recent research interest centered around i*
modelling language, and discuss about possible further directions for i*
related research and practice.
Keywords: i*, iStar, Empirical Study, Taxonomy
1 Intorduction
i* has been widely studied as a social modelling language, centred around the
concepts of goals, actors and social dependencies. It plays a significant role in
modelling organizations, social roles, actors intentions and their interdependen-
cies. People in requirements engineering and information systems engineering
community are publishing research work related to different perspectives of i*.
In order to understand the state of the research better, we retrieved recent pa-
pers from a few major research databases. The objective of this survey study is
to identify the key research issues people are aiming at while study i* language.
We classified the work according to the content and the nature of the study, to
reach a clear understanding on the recent research interest centered around the
i* modelling language, based on which we can identify possible further directions
with more potential for i* research and applications.
– RQ1: What is the basic classification of research studies in the area of
i Star/i *; specifically in Requirements Engineering (RE) field?
– RQ2: What are the challenges with respect to i Star/i * discussed by the
researchers in the studies?
Fig. 1. Detail of SLR : Research Protocol
2 Research Methodology: Systematic Literature Review
We have used Systematic Literature Review (SLR) as a research methodology
for this study. We have used Barbara Kitchenham guidelines [13] for performing
SLR. The detail of the study can be seen in Figure 1.
We have searched Web of Science, Elsevier and Springer for the extraction
of the I-Star related papers. Furthermore, we have searched Engineering Village
for possible retrieval of the studies across different databases. Finally, we have
searched blogs, papers, references and ResearchGate for further addition of pa-
pers. This is done so that we may minimize the biasness in the selection of the
studies and also to get maximum of the studies to start. Figure 1 shows the
detail of SLR protocol.
Table 1. Summary of Findings : Challenges Discussed
Reference Challenges Discussed
Modularity not supported, Scalability Issues.
[1]
Some solutions proposed for scalability and further tested by one case study.
Scalability & Usability challenges.
[2]
Proposed extension for scalability challenge.
[3] Discussed Usability challenge.
[4] Solution discussed to mitigate scalability & Complexity challenges.
[5] Proposed an approach. Scalability still need to be verified.
[6] Scalability Challenges and solution by using modularity.
[7] Discussed iStarML using XML challenges with respect to scalability.
Challenges and tradeoffs regarding i* tools.
[8]
Discussed Usability, model scalability, installation & maintenance challenges.
Tool Usability, i* Tool challenge discussed.
[9]
Discussed Browser compatibility challenges.
[10] Consistency challenges.
[11] Student Adaptability challenge.
Discussed Model Consistency & completeness.
[12]
Game based Learning.
Table 2. Summary of Findings : Classification
Reference Classification
Application in DW, and extended the language by
[1]
modules ->scalability problem of i*
[14] Application in cloud computing, positive
[2] Application in web applications ->Scalability
[15] Application: Tropos Framework for Modeling at high Level.
[16] Application: (i* and combination of Scrum)
[17] Application : Ambient Intelligence App
[18] Application: Social Threat Modeling - Security
[3] Application; KBS
[19] Application: CRS
[20] Application in OSN
[21] Application in OSN
[22] Language (Modeling), i* ->UML class diagram
[4] Language ->textual model ->Scalability
[23] Language ->iStar 2.0
[24] Language ->comparison : i* with DEMO
[25] Language ->comparison : i* with KAOS
[26] Language Tool: iStar and Creativity
[5] Language: Transformation i* ->STREAM-A
[27] Language: Ambiguity
[6] Language: (i* ML 2.0)
[28] Language: Guide i* 2.o
[7] Language: i* JSON
[29] Language: Model repository
[8] Tool: Survey
[9] Tool : Growing Leaf Evolution tool
[30] Technical: Changes impact analysis based on iStar
[31] Technical: Easier Repository of i* based Models
[10] Technical: Identify Consistency Issues in URN Models
[32] Technical : Reasoning of Qualities
[33] Technical: Patterns in IS design
[11] Teaching: Cohorts
[12] Teaching: Extension of iStar
3 Findings
Based on the survey analysis from Table 1, we can see major open problems yet
to be solved with regard to i* modelling language are: the scalability problem,
the clarity problem, and combined use problem. For clarity problem i Star 2.0
has made considerable progress in clarity in modelling syntax and semantics,
where earlier vague and confusing definitions and usage suggestions are polished
and clarified. Scalability problem remains open, but with actor boundary, we
can already separate the analysis of inter-actor relationship analysis and the
inner-actor rational analysis. i*, as an early requirement modelling language, is
often used together with other modelling languages to map high-level intentions
to operational system behaviours or constraints, including, i* with UML class
diagrams, with URN models, with scrum process, with KAOS, with DEMO,
with petri-net. i*, due to its social nature, is fairly feasible in capturing relations
in online social networks, in services modelling, in security, and in knowledge
modelling.
Table 2 explains that the studies included in the SLR on the topic of i*
can be divided into fours main categories. First one is studies focusing on Ap-
plications of i* e.g., Application in a web application, Application in Online
Social Networking and so on. The second type of studies has a focused on lan-
guage/tools related to i*. e.g. creative leaf, language comparison, and language
advancement. The third type of papers focuses on technical aspects of i* e.g.
patterns in Information system design and the last categorization focused on the
teaching/education aspect of the i*. The detail of papers and classification can
be seen in the Table 2.
We have observed during our empirical study that by searching i * or “ i * ”
don’t retrieve the results related to i Star, as in database “*” means any combi-
nation of previous word or string. So from our study we also suggest researchers
must use i Star or i* wordings in keywords, abstract and title of the study; so
that studies may be retrieved with ease.
Acknowledgement
Financial support from the Natural Science and Technology Support Program
project no. 2015BAH14F02, and Natural Science Foundation of China Project
no. 61432020 are gratefully acknowledged.
References
1. Maté, A., Trujillo, J., Franch, X.: Adding semantic modules to improve goal-
oriented analysis of data warehouses using i-star. Journal of systems and software
88 (2014) 102–111
2. Aguilar, J.A., Zaldı́var, A., Tripp, C., Misra, S., Sánchez, S., Martı́nez, M., Garcı́a,
O.V.: A solution proposal for complex web application modeling with the i-star
framework. In: International Conference on Computational Science and Its Appli-
cations, Springer (2014) 135–145
3. Basden, A., Brown, A.J.: Istara tool for creative design of knowledge bases. Expert
Systems 13(4) (1996) 259–276
4. Penha, F., Lucena, M., Lucena, L., Angra, C., Alencar34, F.: A proposed textual
model for i-star. (2016)
5. Pimentel, J., Lucena, M., Castro, J., Silva, C., Santos, E., Alencar, F.: Deriving
software architectural models from requirements models for adaptive systems: the
stream-a approach. Requirements Engineering 17(4) (2012) 259–281
6. Cares, C., López, L.: Towards istarml 2.0: Closing gaps from evolved requirements.
In López, L., Yu, Y., eds.: Proceedings of the Ninth International i* Workshop
co-located with 24th International Conference on Requirements Engineering (RE
2016), Beijing, China, September 12-13, 2016. Volume 1674 of CEUR Workshop
Proceedings., CEUR-WS.org (2016) 91–96
7. Franco-Bedoya, O., Ameller, D., Costal, D., López, L.: istarjson: A lightweight
data-format for i* models. In López, L., Yu, Y., eds.: Proceedings of the Ninth
International i* Workshop co-located with 24th International Conference on Re-
quirements Engineering (RE 2016), Beijing, China, September 12-13, 2016. Volume
1674 of CEUR Workshop Proceedings., CEUR-WS.org (2016) 37–42
8. Li, T., Grubb, A.M., Horkoff, J.: Understanding challenges and tradeoffs in istar
tool development. (2016)
9. Grubb, A.M., Song, G., Chechik, M.: Growingleaf: Supporting requirements evo-
lution over time. In López, L., Yu, Y., eds.: Proceedings of the Ninth International
i* Workshop co-located with 24th International Conference on Requirements Engi-
neering (RE 2016), Beijing, China, September 12-13, 2016. Volume 1674 of CEUR
Workshop Proceedings., CEUR-WS.org (2016) 31–36
10. Akhigbe, O., Amyot, D., Anda, A.A., Lessard, L., Xiao, D.: Consistency analysis
for user requirements notation models. In López, L., Yu, Y., eds.: Proceedings of
the Ninth International i* Workshop co-located with 24th International Conference
on Requirements Engineering (RE 2016), Beijing, China, September 12-13, 2016.
Volume 1674 of CEUR Workshop Proceedings., CEUR-WS.org (2016) 43–48
11. Svee, E.O., Zdravkovic, J.: istar instruction in mixed student cohort environments.
In: iStarT@ CAiSE. (2015) 19–24
12. Oliveira, A.d.P.A., Werneck, V.M.B., do Prado Leite, J.C.S., Cysneiros, L.M.: The
monopoly game to teach eri* c-intentional requirements engineering. In: iStarT@
CAiSE. (2015) 49–54
13. Brereton, P., Kitchenham, B.A., Budgen, D., Turner, M., Khalil, M.: Lessons from
applying the systematic literature review process within the software engineer-
ing domain. Journal of Systems and Software 80(4) (2007) 571 – 583 Software
Performance5th International Workshop on Software and Performance.
14. Oktadimi, N.R., Surendro, K., et al.: Requirements engineering for cloud com-
puting in university using i*(istar) hierarchy method. In: Information Science and
Applications. Springer (2015) 885–890
15. Estrada, H., Najera, K., Vázquez, B., Martı́nez, A., Téllez, J.C., Hierro, J.J.: Ap-
plying tropos modeling for smart mobility applications based on the FIWARE
platform. In López, L., Yu, Y., eds.: Proceedings of the Ninth International i*
Workshop co-located with 24th International Conference on Requirements Engi-
neering (RE 2016), Beijing, China, September 12-13, 2016. Volume 1674 of CEUR
Workshop Proceedings., CEUR-WS.org (2016) 85–90
16. de Araujo, L.B., Siqueira, F.L.: Using i* with scrum: An initial proposal. In López,
L., Yu, Y., eds.: Proceedings of the Ninth International i* Workshop co-located with
24th International Conference on Requirements Engineering (RE 2016), Beijing,
China, September 12-13, 2016. Volume 1674 of CEUR Workshop Proceedings.,
CEUR-WS.org (2016) 19–24
17. Guzman, A., Martı́nez, A., Agudelo, F.V., Estrada-Esquivel, H., Ortega, J.P., Or-
tiz, J.: A methodology for modeling ambient intelligence applications using i*
framework. In López, L., Yu, Y., eds.: Proceedings of the Ninth International i*
Workshop co-located with 24th International Conference on Requirements Engi-
neering (RE 2016), Beijing, China, September 12-13, 2016. Volume 1674 of CEUR
Workshop Proceedings., CEUR-WS.org (2016) 61–66
18. Liu, L., Yu, E., Jabeen, G.: Social threats modelling with i*. In López, L., Yu,
Y., eds.: Proceedings of the Ninth International i* Workshop co-located with 24th
International Conference on Requirements Engineering (RE 2016), Beijing, China,
September 12-13, 2016. Volume 1674 of CEUR Workshop Proceedings., CEUR-
WS.org (2016) 97–102
19. Bouraga, S., Jureta, I., Faulkner, S.: Modelling requirements for content recom-
mendation systems. arXiv preprint arXiv:1606.05746 (2016)
20. Bouraga, S., Jureta, I., Faulkner, S.: Representation of rules for relevant recommen-
dations to online social networks users. In: Artificial Intelligence for Requirements
Engineering (AIRE), 2015 IEEE Second International Workshop on, IEEE (2015)
1–8
21. Bouraga, S., Jureta, I., Faulkner, S.: Requirements engineering patterns for the
modeling of online social networks features. In: Requirements Patterns (RePa),
2014 IEEE 4th International Workshop on, IEEE (2014) 33–38
22. Melo, J., Sousa, A., Agra, C., Júnior, J., Castro, J., Alencar, F.: Formalization
of mapping rules from istar to class diagram in uml. In: Software Engineering
(SBES), 2015 29th Brazilian Symposium on, IEEE (2015) 71–79
23. López, L., Aydemir, F.B., Dalpiaz, F., Horkoff, J.: An empirical evaluation
roadmap for istar 2.0. (2016)
24. Fatyani, T., Iijima, J., Park, J.: Comparing demo with i star: In identifying software
functional requirement. BMSD 2015 (2015)
25. Werneck, V.M.B., Oliveira, A.d.P.A., do Prado Leite, J.C.S.: Comparing gore
frameworks: i-star and kaos. In: WER. (2009)
26. Horkoff, J., Maiden, N.: Creative leaf: A creative istar modeling tool. Proc. of
iStar 16 (2016)
27. López, L., Franch, X., Marco, J.: Making explicit some implicit i* language de-
cisions. In: International Conference on Conceptual Modeling, Springer (2011)
62–77
28. Dalpiaz, F., Franch, X., Horkoff, J.: istar 2.0 language guide. CoRR
abs/1605.07767 (2016)
29. Abad, K., Carvallo, J.P., Espinoza, M., Saquicela, V.: Towards the creation of a
semantic repository of istar-based context models. In: Trends and Applications in
Software Engineering. Springer (2016) 125–137
30. Aguilar, J.A., Tripp, C., Zaldivar, A., Garcia, O., Zurita, C.E.: Evaluating a
requirements change request in a goal-oriented requirements engineering model.
IEEE Latin America Transactions 14(5) (2016) 2411–2417
31. Abad, K., Pérez, W., Carvallo, J.P.: Managing i*-based reusable context models
elements through a semantic repository. In López, L., Yu, Y., eds.: Proceedings of
the Ninth International i* Workshop co-located with 24th International Conference
on Requirements Engineering (RE 2016), Beijing, China, September 12-13, 2016.
Volume 1674 of CEUR Workshop Proceedings., CEUR-WS.org (2016) 67–72
32. Li, F., Liu, L., Mylopoulos, J.: Similarity-based reasoning with quality goals.
In López, L., Yu, Y., eds.: Proceedings of the Ninth International i* Workshop
co-located with 24th International Conference on Requirements Engineering (RE
2016), Beijing, China, September 12-13, 2016. Volume 1674 of CEUR Workshop
Proceedings., CEUR-WS.org (2016) 13–18
33. Abad, K., Carvalho, J.P., Peña, C.: istar in practice: On the identification of
reusable sd context models elements. In: iStar. (2015) 43–48