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Change Requirements: An Explanation of What
Stakeholders Try to Avoid and What They Try to Achieve
Johan F. Hoorn, Elly A. Konijn,H. van Vliet, & G. vd Veer
Vrije Universiteit
Computer ScienceInformation Management and Software Engineering
Contents
Problem Analysis Model Method Case Results Conclusions
Johan F. Hoorn, 2005
M M I 9 9 0 0 9
Analysis Where do change requests come from?
Business model 1 Business model 2 Change in business sub goals - Main goals: Profit - Sub goals: Cost-effectiveness, efficiency
How come business goals change? Change in sub goals (strategic management) - Main goals: Earn my living - Sub goals: Fire employees (not me),
improve IT to guarantee same output
Johan F. Hoorn, 2005
Model Change of Stakeholder Requirements (CoStaR) (Hoorn & Van der Veer, 2003a; 2003b)
One of the hypotheses:
Johan F. Hoorn, 2005
Goals Valence Requirements
Stakeholder evaluation:Does a system feature support my goals?Does a system feature obstruct my goals?(after Frijda, 1986)
Method REquest, the Requirements Engineering questionnaire
General approach: Items that combine
- a must or a won’t requirement, with- support or obstruction of- a goal to achieve with the system or a goal state to avoid,
scored for agreement on a 6-point rating scale
Johan F. Hoorn, 2005
Case Eighteen managers of a logistic warehouse management system
must/won’t support/obstruct goal approach/avoid
E-mail ordering increases efficiencyE-mail ordering decreases efficiencyE-mail ordering increases inefficiencyE-mail ordering decreases inefficiencyPaper ordering forms increase efficiencyPaper ordering forms decrease efficiencyPaper ordering forms increase inefficiencyPaper ordering forms decrease inefficiency
Johan F. Hoorn, 2005
Example items
Results (1) Original hypothesis:
Johan F. Hoorn, 2005
Goals Valence Requirements
- Indeed, goals, valence, and requirements all evoked significant effects on agreement to requirements statements
Results (2)
Johan F. Hoorn, 2005
MANOVA (must vs won’t) * (support vs obstruct) * (goal approach vs avoid)Pillai’s Trace = .51, F(2,16)= 8.40, p= .003, ηp
2= .51
↑ Grand mean agreement
(.98)
(1.09)
(1.44)
(1.04)
(1.14)
(.96)2.19
2.41
1.8
2.78
3.67
2.5
0
1
2
3
4
5
Requirements(must have)
Requirements(won't have)
Valence(support)
Valence(obstruct)
Goals (toapproach)
Goals (toavoid)
Results (3) Original hypothesis:
Johan F. Hoorn, 2005
Goals Valence Requirements
- Bipolar conception does not hold Regression: R2= .03, R2
adj= -.03, F(1,16)= .47, p= .504
Goals(avoid)
Valence(obstruct)
Requirements(won’t have)
Goals(approach)
Valence(support)
Requirements(must have)
- Goal-driven RE models should be unipolar
Results (4) However, original structure should be completely revised
Johan F. Hoorn, 2005
Goals(to approach)
Requirements(won’t have)
Valence(support)
Valence(obstruct)
Goals(to avoid)
Requirements(must have)
Results (5)
Johan F. Hoorn, 2005
R2= .93, R2adj= .90
F(5,12)= 30.30, p= .000
no predictive power
no predictive power
Requirements vs. goals: Parameter coefficient= -.56, t= -4.04, p= .001, ηp2= .49
Yet, valence does have influence. Valence is a moderator!
R2= .79, R2adj= .70
F(5,12)= 9.01, p= .001
90%!!
Requirements(won’t have)
Requirements(must have)
Valence(support)
Valence(support)
Goals(approach)
Goals(avoid)
70%!!
Conclusions (1)
RE should be oriented to goals Requirements validation should be done with structured questionnaires (e.g., REquest) Goals to achieve predict won’t requirements Goal states to avoid predict must requirems Like the weather, valence does not predict mood (i.e. agreement) but it does influence it
Johan F. Hoorn, 2005