Demo Data from EDBT 2026 / reviewers in the wild / expert
Arda Gureller
dblp:200/2828
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 1 · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Software engineering, system software, and programming languages
1 paper |
Empirical software engineering · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Empirical software engineering › human factors in software engineering
confirmation bias |
0.6 | 1 | 2022 | What Leads to a Confirmatory or Disconfirmatory Behavior of Software Testers? · IEEE Trans. Software Eng. 2022 |
Empirical software engineering
developer studies |
0.2 | 1 | 2022 | What Leads to a Confirmatory or Disconfirmatory Behavior of Software Testers? · IEEE Trans. Software Eng. 2022 |
Empirical software engineering › qualitative research
grounded theory |
0.2 | 1 | 2022 | What Leads to a Confirmatory or Disconfirmatory Behavior of Software Testers? · IEEE Trans. Software Eng. 2022 |
Methods — techniques the papers use, named apart from their topics
semi-structured interviews · 0.6grounded theory · 0.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | What Leads to a Confirmatory or Disconfirmatory Behavior of Software Testers?abstractBackground:The existing literature in software engineering reports adverse effects of confirmation bias on software testing. Confirmation bias among software testers leads to confirmatory behavior, which is designing or executing relatively more specification consistent test cases (confirmatory behavior) than specification inconsistent test cases (disconfirmatory behavior).Objective:We aim to explore the antecedents to confirmatory and disconfirmatory behavior of software testers. Furthermore, we aim to understand why and how those antecedents lead to (dis)confirmatory behavior.Method:We follow grounded theory method for the analyses of the data collected through semi-structured interviews with twelve software testers.Results:We identified twenty antecedents to (dis)confirmatory behavior, and classified them in nine categories. Experience and Time are the two major categories. Experience is a disconfirmatory category, which also determines which behavior (confirmatory or disconfirmatory) occurs first among software testers, as an effect of other antecedents. Time Pressure is a confirmatory antecedent of the Time category. It also contributes to the confirmatory effects of antecedents of other categories.Conclusion:The disconfirmatory antecedents, especially that belong to the testing process, e.g., test suite reviews by project team members, may help circumvent the deleterious effects of confirmation bias in software testing. If a team’s resources permit, the designing and execution of a test suite could be divided among the test team members, as different perspectives of testers may help to detect more errors. The results of our study are based on a single context where dedicated testing teams focus on higher levels of testing. The study’s scope does not account for the testing performed by developers. Future work includes exploring other contexts to extend our results. Iflaah Salman, Pilar Rodríguez 0002, Burak Turhan, Ayse Tosun Misirli, Arda Gureller |
IEEE Trans. Software Eng. | 5 |