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 Science Information Management and Software Engineering

Contents  Problem  Analysis  Model  Method  Case  Results  Conclusions Johan F. Hoorn, 2005 M M I

Problem  How can requirements change be anticipated? Johan F. Hoorn, 2005

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 ValenceRequirements 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’tsupport/obstructgoal approach/avoid orderingincreasesefficiency orderingdecreasesefficiency orderingincreasesinefficiency orderingdecreasesinefficiency Paper ordering formsincreaseefficiency Paper ordering forms decreaseefficiency Paper ordering forms increaseinefficiency Paper ordering forms decreaseinefficiency Johan F. Hoorn, 2005 Example items

Results (1)  Original hypothesis: Johan F. Hoorn, 2005 Goals ValenceRequirements - 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, η p 2 =.51 ↑ Grand mean agreement (.98) (1.09) (1.44) (1.04) (1.14) (.96) Requirements (must have) Requirements (won't have) Valence (support) Valence (obstruct) Goals (to approach) Goals (to avoid) 

Results (3)  Original hypothesis: Johan F. Hoorn, 2005 Goals ValenceRequirements - Bipolar conception does not hold Regression: R 2 =.03, R 2 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 R 2 =.93, R 2 adj =.90 F (5,12) = 30.30, p=.000 no predictive power Requirements vs. goals: Parameter coefficient= -.56, t= -4.04, p=.001, η p 2 =.49 Yet, valence does have influence. Valence is a moderator! R 2 =.79, R 2 adj =.70 F (5,12) = 9.01, p= %!! 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

Conclusions (2)  Most important RE questions are:  What are the things you want to achieve with the system?  What should the system NOT have to support that?  What are the things you want to avoid with the system?  What should be ON the system to support that? Johan F. Hoorn, 2005