1. R EFLECTIVE A NALYSIS OF THE S YNTAX AND S EMANTICS OF THE i* F RAMEWORK Jennifer Horkoff, Golnaz Elahi, Samer Abdulhadi, Eric Yu Department of Computer Science and Faculty of Information University of Toronto, Canada RIGiM’08

2. M ODELING L ANGUAGES : I NTENTION VS. U SE Modeling languages are introduced to serve a variety of purposes, including: Facilitating communication Making tacit information explicit Storing knowledge Aiding analysis (Sometimes the intention of a language is not explicitly expressed) 2

3. M ODELING L ANGUAGES : I NTENTION VS. U SE As a language is adopted and used, it may be used in ways which the language creators did not anticipate It is useful to reflect on the intentions of the language versus its use in practice We focus on the intentions of the syntax and semantics of a language 3 Reflective Analysis of intention vs. use can help to answer: What were the original intentions of the language syntax and semantics? How are the syntax and semantics being commonly used? Why are users prone to deviate from the original language description? Do these variations matter? Should the language be modified? Or, should an effort be made to increase training? Reflective Analysis of intention vs. use can help to answer: What were the original intentions of the language syntax and semantics? How are the syntax and semantics being commonly used? Why are users prone to deviate from the original language description? Do these variations matter? Should the language be modified? Or, should an effort be made to increase training?

4. R EFLECTIVE A NALYSIS OF THE i* F RAMEWORK We analyze the intention vs. use of the i* Framework i* is a goal and agent-oriented framework which was intended to be used in the early requirements stage to capture agents, their inter-relationships, and their goals Aimed at helping to discover and compare high-level system design alternatives 4

5. i* E VOLVING A good candidate for reflective analysis 5 The i* Framework was left open to interpretation and modification i* has been applied to many areas for differing purposes We compare i* usage to current U of T Style i* is used in system analysis courses i* Adapted Surveyed student i* assignments, research papers and presentations

6. S URVEY M ETHOD Survey subjects looking for variations from U of T style: 15 student project assignments from a graduate level system analysis course 15 academic papers and presentations using i* drawn from various sources. All models in each document were surveyed Variations were only counted once per document The models covered diverse application domains, including health care, banking, and education systems. An analysis of the motivations behind the variations was also performed Was the modeler confused about the syntax? Was the modeler using a syntactic shortcut? Does the variation indicate issues within i*? 6

7. T HE i* F RAMEWORK : U OF T F LAVOUR 7 Elements Links between Elements Actors and Actor Boundaries Actor Association Links Hard Soft

8. T HE i* F RAMEWORK : U OF T F LAVOUR 8 Syntax Restrictions Include: Goals decompose only with means- ends links to tasks Decomposition links are only used from tasks Dependums are needed Dependency links must go outside actors Actors are not nested Contribution links only go to softgoals Contribution links only inside actors Actor Associations are restricted between certain actors

9. S URVEY R ESULTS Variations were grouped together in two ways: By syntax category By perceived motivation 9

10. 10 S URVEY R ESULTS : V ARIATION I NSTANCES BY S YNTAX C ATEGORY Number of Variations in Category 868544

11. D ECOMPOSITION L INKS V ARIATIONS 11 Decomposition links are drawn directly from goals to tasks Decomposition links are used between goals Softgoals are decomposed to tasks Goals are means- ends decomposed to softgoals Decomposition links extend outside actors' boundaries Decomposition links are used between resources Goals are decomposed to resources Decomposition links are used between Softgoals 9 6 5 4 3 2 1 1

12. S URVEY R ESULTS Variations Grouped by perceived motivations: 12 Perceived Motivation The Nature of “Hard” Elements and Softgoals Means-Ends vs. Decomposition The Nature of Actor Boundaries Potentially Ambiguous Dependencies Understanding Associations Intermediate Model Stages Resource Refinement Association Links vs. Inclusion Dependums Incomplete Evaluation Total Number of Variations 15 6 4 1 1 2 3 1 1 1 35 Instances 70 24 14 8 5 3 2 1 1 1 129

13. E XAMPLE V ARIATION : N ATURE OF “H ARD ” E LEMENTS AND S OFTGOALS G OAL (M EANS -E NDS ) D ECOMPOSED TO S OFTGOAL (7 I NSTANCES ) Syntax not permitted in the U of T style of i* Semantics: The nature of soft and hard goals implies that a softgoal should not be sufficient to satisfy a hard goal Something qualitative satisfies something concrete However… In i* a task can be decomposed to a softgoal The softgoal represents a quality the task should encompass 13

14. E XAMPLE V ARIATION : N ATURE OF “H ARD ” E LEMENTS AND S OFTGOALS G OAL (M EANS -E NDS ) D ECOMPOSED TO S OFTGOAL Possible Responses: Discontinue decomposition of tasks to sofgoals But how do we associate a quality with a task? Create an alternative way to associate qualitative aspects to tasks, other than through decomposition Could also be used for goals? 14 Alternative Syntax

15. S URVEY R ESULTS Variations Grouped by perceived motivations: 15 Perceived Motivation The Nature of “Hard” Elements and Softgoals Means-Ends vs. Decomposition The Nature of Actor Boundaries Potentially Ambiguous Dependencies Understanding Associations Intermediate Model Stages Resource Refinement Association Links vs. Inclusion Dependums Incomplete Evaluation Total Number of Variations 15 6 4 1 1 2 3 1 1 1 35 Instances 70 24 14 8 5 3 2 1 1 1 129

16. E XAMPLE V ARIATION : M EANS -E NDS VS. D ECOMPOSITION G OAL D ECOMPOSITION (16 INSTANCES ) Syntax: Goal decomposition is not permitted in the U of T i* style Semantics: Tasks versus goals Goals can be accomplished in different ways Task is a particular way of doing something Syntax restriction promotes the discovery of alternatives 16

17. E XAMPLE V ARIATION : T HE N ATURE OF A CTOR B OUNDARIES C ONTRIBUTION L INKS O UTSIDE B OUNDARIES (6 I NSTANCES ) Syntax: Only dependency links should be used outside actor boundaries Semantics: Emphasize actors’ autonomy Actors should not have knowledge of the internal motivations of other actors 17

18. P OSSIBLE R ESPONSES Strict and loose versions of i* syntax: Strict syntax follows the U of T style restrictions Loose syntax relaxes a select set of rules based on common variations: Means-ends for tasks, decomposition for goals Contribution links across actors Omitting dependums The notion of syntactical shortcuts 18 Shortcut for

19. S URVEY R ESULTS : S TUDENTS V S R ESEARCHERS Students are more likely to: Have more difficulties understanding the difference between soft and “hard” elements Have incomplete models (models with un-decomposed goals) Misuse association links Researchers are more likely to adapt the Framework as they see fit: More likely to use non-dependency links outside of actor boundaries 19

20. C ONCLUSIONS AND F UTURE W ORK Based on an analysis of several variations we were able to suggest: Areas where the syntax of i* could be modified We would like to explore the notion of “loose” and “strict” versions of i* syntax Recognized syntactic shortcuts Associating softgoals with hard elements Areas where more training is needed Soft vs. “hard” elements Association links Consistent interpretation of standard syntax shortcuts Future work can: Expand our survey pool and include analysis of further variations Experiment with the utility of modified i* syntax 20

21. T HANK Y OU Jennifer Horkoff jenhork@cs.utoronto.ca www.cs.utoronto.ca/~jenhork Golnaz Elahi elahi@cs.utoronto.ca www.cs.utoronto.ca/~elahi Samer Abdulhadi Eric Yu eric@cs.utoronto.ca www.cs.utoronto.ca/~eric i* Wiki http://istar.rwth-aachen.de/tiki-view_articles.php 21

22. T HREATS TO V ALIDITY The selection of academic papers and presentations was not completely random The surveyor was less interested in papers without variations Student assignments were longer than academic works, and had more examples But not all variations were higher for student assignments The qualitative analysis of the variations was performed by the authors Variation intentions could be misinterpreted However, misinterpretation could indicate a general source of confusion 22

23. T HE N ATURE OF “H ARD ” E LEMENTS AND S OFTGOALS Variation# Instances Decomposition links are used between softgoals3 Softgoals are decomposed to tasks2 Means-ends links are used between softgoals1 Softgoal dependency is met by a goal5 Softgoal dependency is met by a task2 Goals are means-ends decomposed to softgoals2 Goals are decomposed to softgoals5 Contribution links are drawn from softgoals to tasks4 Contribution links are drawn from softgoals to goals2 Contribution links are used between goals1 Contribution links are drawn from resources to tasks1 Softgoal should be goal10 Goal should be softgoal15 Task should be softgoal8 Softgoal should be task7 Total70 We select one category of perceived motivation to examine in detail 23 Goal (means-ends) decomposed to softgoal

24. S URVEY R ESULTS : D ECOMPOSITION L INKS E XAMPLE B REAKDOWN 24 VariationAssignmentsAcademic WorkTotal Instances Decomposition links are drawn directly from goals to tasks 549 Decomposition links are used between goals 426 Goals are means-ends decomposed to softgoals 235 Decomposition links extend outside actors' boundaries 134 Decomposition links are used between Softgoals 213 Softgoals are decomposed to tasks 202 Decomposition links are used between resources 101 Goals are decomposed to resources 011 Resources to tasks are decomposed to tasks 000 Total 17 1431

25. S URVEY R ESULTS Variations Grouped by perceived motivations: 25 Number of Variations in Category Total Instances per Category