The document presents work on an intelligent approach for goal-oriented software requirements analysis. It discusses objectives like analyzing research issues in software goal models and prioritizing stakeholders. A method called RAGOSRA is proposed using rough set theory to analyze software requirements. A case study is presented to demonstrate applying RAGOSRA which involves identifying goals, evaluating them by stakeholders, computing ranking values using rough set concepts, and analyzing goals. The work contributes a method using rough sets for goal-oriented requirements analysis.

1. Presented By Under the Guidance of
Farhana Mariyam Prof. Shabana Mehfuz (Supervisor)
Ph. D. Research Scholar Dr. Mohd. Sadiq (Co-Supervisor)
Student Id.:20188802
Department of Electrical Engineering
Faculty of Engineering and Technology
Jamia Millia Islamia
New Delhi-110025
An Intelligent Approach For Goal Oriented
Software Requirements Analysis

2. Table of Contents
1.Introduction
2.Objectives
3.Work done in the last 6 months
i. Introduction
ii. Related Work
iii. Proposed Method
iv. Case Study
4.Conclusion and Future Work
5.References

3. Objectives
• Parameter analysis of various research issue in the area of software goal models.
• Formulation of intelligent technique for prioritization of stakeholders on the
basis of the importance of the software requirements.
• To propose a method for the elicitation of attributed values of goal models using
intelligent techniques.
• Development of supportive tool to enhance adaptability of proposed method.
• Comparative analysis of various methods proposed for Goal Oriented Software
Requirements Analysis.

4. Farhana Mariyam, Shabana Mehfuz, and Mohd. Sadiq, “Classification and Evaluation of Goal Oriented Requirements Analysis Methods”,
International Conference on Applied Soft computing and Communication Networks (ACN'20), October 14-17, 2020, Chennai, India.
(Published in :Springer Lecture Notes in Networks, Syst., Vol. 187, SabuM. Thampi et al. (Eds): Applied Soft Computing and Communication Networks,
978-981-33-6172-0, 501509_1_En, (Chapter 21)).
In our previous work, towards Objective 1
i. classification of GORA methods into five sub-process and focus on one of the
key sub-processes of GORE, i.e., goal oriented requirements analysis (GORA).
ii. we have classified methods into three parts, i.e., GORA methods for the
elicitation and analysis of FRs and NFRs, GORA dedicated to NFRs only, and
GORA method for social modeling.
iii. evaluation of GORA methods based on goal concepts, goal links, and soft
computing techniques used in the development of the intelligent GORA
methods.

5. Farhana Mariyam, Shabana Mehfuz, and Mohd. Sadiq, “SelectGoREATech: Selection of Goal-Oriented Requirements Elicitation and
Analysis Techniques ”, 7th International Conference on Computations in Engineering and Technology (ICCET 2022 ), February 12-13, 2022, Lonere,
Maharastra, India.
Work towards Objective 2
• Existing studies do not support the goal-oriented techniques.
• A method has been developed for the selection of SRs elicitation techniques based on
goal-oriented concepts namely
SelectGoREATech

6. Several techniques have been developed using goal concepts for the analysis of the
software requirements, i.e.,
• AGORA Crisp data
• FAGOSRA Fuzzy Logic –> Prior information required
• lacks objectivity
• affect the ranking values of the requirements during the analysis
• Therefore, to address this issue a method has been developed using roughset
theory for the analysis of the requirements in goal-oriented software
requirements analysis process and named as RAGOSRA (Rough Attributed
Goal Oriented Software Requirements Analysis Method)

7. Introduction
• (RE) which is concerned with the identification, modeling, analysis, verification, validation, and management
of software requirements Research in the area of RE has been classified into goal-oriented RE
• aspect-oriented RE
• agent oriented RE
• security-threat oriented RE
• situation-oriented RE
• fuzzy logic oriented RE
• Limitations of the fuzzy based methods prior information is required during the decision-
making process.
• Lacks objectivity and may affect the ranking values of the requirements during the analysis
process.
• Therefore, to address this issue, our work presents a rough attributed goal-oriented software
requirements analysis (RAGOSRA) method.

8. • The contributions of our work are as follows:
• 1. A method has been developed using rough-set theory for the analysis of the
requirements in goal-oriented software requirements analysis process. Two
attributed values such as rough contribution values and rough preference matrices
have been introduced during the analysis
• 2. A comparative study is presented to demonstrate the applicability of the
proposed method.

9. Related work
Goal-oriented requirements analysis methods
S. No. GORA Methods (Year) Authors Data used in
analysis
1 KAOS (1990) Lamsweerde [9] Crisp data
2 NFR framework (1992) Mylopoulos et al. [10] Crisp data
3 AGORA (2002) Kaiya et al. [12] Crisp data
4 PRFGORE process (2014) Sadiq and Jain [8,14] Fuzzy data
5 FAGOSRA (2016) Mohammad et al. [13] Fuzzy data
6 GOASREP using AHP/2016 Garg et al. [15] Crisp data
7 FLDSREP/2022 Javed et al. [16] Fuzzy data
Table 1: Goal-oriented requirements analysis methods

10. Related work…
An insight into rough-set theory
Rough set theory,
• introduced by Zdzislaw Pawlak in the early 1980s
• deals with vagueness and uncertainty
• does not need any preliminary or additional information about data
• Based on sets—lower and upper approximations
• 𝐹𝐴 = {𝑥 ∈ 𝑈𝑜𝐷:[𝑥]𝐹 ⊆ 𝐴} (1)
• ̅𝐹𝐴 = {𝑥 ∈ 𝑈𝑜𝐷: [𝑥]𝐹 ∩ 𝐴 ≠ ∅} (2)

11. Fig. 1. Lower and upper approximations of a rough set

12. Proposed Method (RAGOSRA)
• The proposed method includes the following steps:
 Step 1: Applying the traditional and goal-oriented method for the
elicitation of the functional and non-functional goals it produces the
functional goal (FG) and non-functional goal (NFG) of a system.
 Step 2: Evaluation of the functional and non-functional goals by decision
makers to evaluate the FGs and NFGs by different stakeholders
 Step 3: Detect the discordances among the stakeholders and goalsto
detect the discordances among stakeholders and goals

13.  Step 4: Compute the ranking value of each goal using rough set theory
 𝐿𝑜𝑤𝐴𝑝𝑟𝑜𝑥 (𝐹𝐺𝑖 ) = ∪ {H ∈ U/F (H) ≤ 𝐹𝐺𝑖 }
 𝑈𝑝𝑝𝐴𝑝𝑝𝑟𝑜𝑥(𝐹𝑅𝑖 ) =∪ {H ∈ U/F (H) ≥ 𝐹𝑅𝑖 }
 Similarly, the lower approximation of 𝑁𝐹𝐺𝑖 , 𝑖. 𝑒. ,
 (𝐿𝑜𝑤𝐴𝑝𝑟𝑜𝑥(𝑁𝐹𝐺𝑖)) and upper approximation of 𝑁𝐹𝐺𝑖 , 𝑖. 𝑒. ,
 (𝑈𝑝𝑝𝐴𝑝𝑟𝑜𝑥(𝑁𝐹𝐺𝑖)) can be defined as: 𝐿𝑜𝑤𝐴𝑝𝑟𝑜𝑥 (𝑁𝐹𝐺𝑗) = ∪ {P ∈ U/N(P) ≤ 𝑁𝐹𝐺𝑗 }
(5) 𝑈𝑝𝑝𝐴𝑝𝑟𝑜𝑥(𝑁𝐹𝐺𝑗) = ∪ {P ∈ U/N (P) ≥ 𝑁𝐹𝐺𝑗 }
 The rough number for each FG and NFG is computed as:
 𝐿𝑜𝑤𝐿𝑡(𝐹𝐺𝑖 ) = 1 𝐽𝐿 ∑ 𝐹(𝐻) |𝐻 ∈ 𝐿𝑜𝑤𝐴𝑝𝑟𝑜𝑥 (𝐹𝐺𝑖 )
 𝐿𝑜𝑤𝐿𝑡(𝑁𝐹𝐺𝑗) = 1 𝑄𝐿 ∑ 𝑁 (𝑃) |𝑃 ∈ 𝐿𝑜𝑤𝐴𝑝𝑟𝑜𝑥 (𝑁𝐹𝑅𝑗)
 𝑈𝑝𝐿𝑡(𝐹𝐺𝑖 ) = 1 𝐽𝑈 ∑ 𝐹 (𝐻) |𝐻 ∈ 𝑈𝑝𝑝𝐴𝑝𝑟𝑜𝑥 (𝐹𝐺𝑖 )
 𝑈𝑝𝐿𝑡(𝑁𝐹𝐺𝑗) = 1 𝑄𝑈 ∑ 𝑁 (𝑃) |𝑃 ∈ 𝑈𝑝𝑝𝐴𝑝𝑟𝑜𝑥 (𝑁𝐹𝐺𝑗)
 Step 5: Analyse the goals based on the ranking values

14. Case Study
• The implementation of the RAGOSRA method is as follows:
• Step 1: After the completion of the requirements elicitation process, following sub-goals
(SGs) of an institute examination system have been identified:
• SG1: ‘‘The system should be economic (NFG1)’’,
• SG2: ‘‘There should be a Login module (FG1)’’,
• SG3: ‘‘Teachers and Administrative module (FG2)’’
• SG4: ‘‘Fee submission module (FG3)’’
• SG5: ‘‘Student module for the activities of the students (FG4)’’,
• SG6: ‘‘The system should be secure (NFG2)’’, and
• SG7: ‘‘The system should be reliable (NFG3)’’.

15. • Step 2: In our work, we have adopted the data of the evaluation of the FGs based
on NFGs and it is Evaluation of four FGs based on three NFGs under fuzzy-set
environment
Table 2: Evaluation of four FGs based on three NFGs under fuzzy-set environment

16. Table 3: Evaluation of four FGs based on three NFGs under rough-set environment
Note: (), {}, and [] represent crisp values, TFNs and rough numbers, respectively.

17. Table 4: Importance weight of NFGs by three stakeholders

18. Table 5: Rough-set representation of importance weight of NFGs by three
stakeholders

19. • Step 3: In this step we have adopted the preference matrix to check the
discordances among the stakeholders
Table 6: Preference matrix of stakeholders

20. Table 7: Rough-set based preference matrix

21. Step 4: Compute the ranking value of each goal using rough set theory

22. • Step 5: Analyse the goals based on the ranking values

23. Conclusion and Future Work

24. References
1. B. H. C. Cheng and J. M. Atlee, "Research Directions in Requirements Engineering," Future of
Software Engineering (FOSE '07), 2007, pp. 285-303
2. Horkoff, J., Aydemir, F.B., Cardoso, E. et al. Goal-oriented requirements engineering: an extended
systematic mapping study. Requirements Eng 24, 133–160 (2019).
3. A. Rashid, P. Sawyer, A. Moreira and J. Araujo, "Early aspects: a model for aspect-oriented
requirements engineering," Proceedings IEEE Joint International Conference on Requirements
Engineering, 2002, pp. 199-202.
4. Y. Singh, A. Gosain and M. Kumar, "Evaluation of Agent Oriented Requirements Engineering
Frameworks," 2008 International Conference on Computer Science and Software Engineering, 2008,
pp. 33-38, doi: 10.1109/CSSE.2008.1555.
5. Ansari MTJ, Pandey D, Alenezi M, STORE: Security Threat Oriented Requirements Engineering
Methodology, Journal of King Saud University - Computer and Information Sciences, Vol. 32, Issue
2, pp. 191-203, 2022.
6. Atukorala NL, Aspect Oriented Requirements Engineering, Ph.D. Thesis, Computer Science, 2019,
Lowa State University, USA.
7. Sadiq M., Fuzzy Logic Driven Goal Oriented Requirements Elicitation Process, Ph.D. Thesis,
Computer Engineering, 2017, National Institute of Technology Kurukshetra, India.

25. References
8. Sadiq M, Jain SK (2015) A fuzzy based approach for the selection of goals in goal-oriented
requirements elicitation process. Int J Syst Assur Eng Manag 6(2):157–164.
9. Zickert F, "Evaluation of the Goal-Oriented Requirements Engineering Method KAOS" AMCIS
2010 Proceedings.
10. Mylopoulos J, Chung L, Nixon B (1992) Representing and using non-functional requirements: a
process-oriented approach. IEEE Trans Softw Eng 18(6):483–497
11. Yu ESK (1997) Towards modeling and reasoning support for early-phase requirements engineering.
In: 3rd IEEE international symposium on requirements engineering. pp 226–235.
12. Kaiya H et al. (2002) AGORA: Attributed Goal Oriented Requirements Analysis, Proceedings of the
IEEE joint International Conference on Requirements Engineering.
13. Mohammad, C.W., Shahid, M. & Hussain, S.Z. Fuzzy attributed goal-oriented software requirements
analysis with multiple stakeholders. Int. j. inf. tecnol. 13, 1–9 (2021).
14. Sadiq M, Jain SK (2014) Applying fuzzy preference relation for requirements prioritization in goal-
oriented requirements elicitation process. Int J Syst Assur Eng Maint 5(4):711–723
15. Garg N, Sadiq M, Agarwal P (2016) GOASREP: Goal oriented approach for software requirements
elicitation and prioritization using analytic hierarchy process. In: 5th international conference on
frontiers in intelligent computing theory and applications. Springer, Singapore

26. Thank You!
(Farhana Mariyam)
Ph. D. Research Scholar
Department of Electrical Engineering
Faculty of Engineering and Technology
Jamia Millia Islamia, New Delhi-110025