From a gambit to a defense with SwEDeL: an approach to defend software estimates from pressure
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Universidade Federal do Amazonas
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The estimation of software projects and tasks is a critical activity in software development and maintenance. Ultimately, people develop and maintain software to satisfy business goals. A problem arises when software estimates collide with such goals: software practitioners deliberately change their estimates because of objectives outside the estimation context, yielding to pressure over their estimates, leading to product and life quality issues. This reveals the behavioral side of software estimation: its results are affected by cognitive and social aspects, requiring more than technical skills to achieve success. Unfortunately, software professionals do not possess the skills needed to defend their estimates from pressure, even though they are the ones with enough technical knowledge to assess whether a business goal is feasible. Such situations lead to the establishment of unrealistic commitments. So, in this work our goal is to provide support to estimators in defending their estimates and negotiating realistic commitments when they face pressure over their estimates. We adopted a Design Science Research (DSR) approach to pursue it. We investigated the factors affecting expert judgment estimation through a Systematic Literature Mapping (SLM), filtering the ones closely related to deliberate changes of estimates, pressure, and the establishment of commitments. This allowed us to better understand these topics in the current research literature as part of the DSR relevance cycle. We also executed a qualitative study about the interaction of estimates and establishing commitments in the software industry to gain the practice’s perspective as part of the DSR relevance cycle. We found evidence on how practitioners change their estimates to make them acceptable to other project stakeholders and use padding as a tool during the establishment of commitments, instead of defending their estimates and negotiating more realistic commitments. With the knowledge we gained from these studies and from a DSR rigor cycle focused on negotiation methods, we proposed an artifact as part of our DSR design cycle. The artifact, entitled SwEDeL (Software Estimates’ Defense Lenses), is a set of lenses that embodies principles from negotiation to help estimators to change their passive posture of yielding to pressure to a more active attitude of engaging with other stakeholders, to better grasp their interests and needs, gain deeper understanding on how the estimate collides with business goals, and to look for alternatives to satisfy their customers and managers’ interests without compromising their own. We assessed SwEDeL through a focus group and then created a digital simulation to present in a more dynamic format. The lenses and the digital simulation are a behavioral intervention to improve software practitioners’ negotiation skills, empowering them to face pressure: a concrete step towards Behavioral Software Engineering. Finally, we assessed the digital simulation and SwEDeL in a controlled experiment with practitioners from the software industry. We collected data on participants’ attitudes, subjective norms, perceived behavioral control, and intentions to perform the defense of their estimates in light of the Theory of Planning Behavior. Results show improved scores among experimental group participants after engaging with the digital simulation and learning about the lenses. They were also more inclined to choose a defense action when facing pressure scenarios than a control group. Practitioners also perceived the set of lenses as useful in their current work environments. Collectively, these results show the effectiveness of the proposed approach and its perceived relevance for the industry.
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MATSUBARA, Patrícia Gomes Fernandes. From a gambit to a defense with SwEDeL: an approach to defend software estimates from pressure. 2022. 213 f. Tese (Doutorado em Informática) - Universidade Federal do Amazonas, Manaus (AM), 2022.
