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A key goal of software engineering research is to improve the environments, tools, languages, and techniques programmers use to efficiently create quality software. Successfully designing these tools and demonstrating their effectiveness involves engaging with tool users — software engineers. Researchers often want to conduct user studies of software engineers to collect direct evidence. However, running user studies can be difficult, and researchers may lack solution strategies to overcome the barriers, so they may avoid user studies. To understand the challenges researchers face when conducting programmer user studies, we interviewed 26 researchers. Based on the analysis of interview data we contribute: (i) a taxonomy of 18 barriers researchers encounter; (ii) 23 solution strategies some researchers use to address 8 of the 18 barriers in their own studies; and (iii) 4 design ideas, which we adapted from the behavioral science community, that may lower 8 additional barriers. To validate the design ideas, we held an in-person all-day focus group with 16 researchers.
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Visualizations for User-supported State Space Exploration of Goal Models
Automated analysis has been used in goal-oriented requirements engineering (GORE) to evaluate scenarios and make trade-off decisions. For higher complexity problems (e.g., backwards analysis), using a search-based solver may be more efficient than custom algorithms. When these black-box solvers produce a single solution, users may be suspicious about whether the given answer is ideal or believable. Users would like to explore the potential solutions but are prevented from doing so because these inquiries often suffer from a state explosion problem. In this RE@Next! paper, we introduce the use of valuation-based filtering and coloring to assist users in understanding a solution space and selecting custom states from it. We use the concrete semantics of modeling requirements in the Evolving Intentions framework and its associated goal modeling tool, BloomingLeaf, to explore the application of these visualization techniques. In our initial evaluation, we demonstrate how these techniques can be used on a fully worked out example. We conduct initial measurements of the time savings and state space reduction created by the valuations and color filtering, and discuss future directions of this project.
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- Award ID(s):
- 2104732
- PAR ID:
- 10450412
- Publisher / Repository:
- 2023 IEEE 31st International Requirements Engineering Conference (RE)
- Date Published:
- ISBN:
- 979-8-3503-2689-5
- Format(s):
- Medium: X
- Location:
- Hannover, Germany
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/RE57278.2023.00036
