Demo Data from EDBT 2026 / reviewers in the wild / expert
Zamira Kholmatova
dblp:278/0274
· DBLP profile ↗
6ranked-venue papers
3as first author
5since 2021 · last 2025
0000-0003-1688-1183ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 3 · 2 first-author · 3 since 2021Software engineering, systems software and programming languages · 2 · 1 first-author · 1 since 2021Databases, data management, data science and information retrieval · 1 · 1 since 2021Applied, interdisciplinary, general and emerging computing · 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% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Energy-efficient computing · 100% |
Topics — the 1 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Energy-efficient computing › power management
mobile device energy |
0.1 | 1 | 2020 | Impact of programming languages on energy consumption for mobile devices · ESEC/SIGSOFT FSE 2020 |
Methods — techniques the papers use, named apart from their topics
meta-analysis · 0.9
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Optimizing Python Code Metrics Feature Reduction Through Meta-Analysis and Swarm Intelligence
Marina Ivanova, Zamira Kholmatova, Nikolay Pavlenko |
MODELSWARD | 2 |
| 2024 | Teaching Empirical Methods to Software Engineers
Zamira Kholmatova, Giancarlo Succi, Navruza Tulkunova |
KES-AMSTA | 1 |
| 2024 | Teaching Lean Software Development to Software Engineers
Zamira Kholmatova, Giancarlo Succi, Navruza Tulkunova |
KES-AMSTA | 1 |
| 2022 | A Meta-analytical Comparison of Naive Bayes and Random Forest for Software Defect Prediction
Ch Muhammad Awais, Gcinizwe Dlamini, Zamira Kholmatova, Giancarlo Succi |
ISDA (3) | 4 |
| 2022 | Meta-analytical comparison of energy consumed by two sorting algorithms
Gcinizwe Dlamini, Firas Jolha, Zamira Kholmatova, Giancarlo Succi |
Inf. Sci. | 3 |
| 2020 | Impact of programming languages on energy consumption for mobile devicesabstractMobile devices are part of our life and their energy consumption poses significant limits to their further adoption and usage. In this work, we conduct a meta-analytical review of the impact of programming languages on the energy consumption of such devices. We consider as a null hypothesis that from the perspective of the consumption of energy, there is no difference in writing apps in C, C++, and Java. With the studies at hand, we conclude that we cannot reject such null hypotheses. Zamira Kholmatova |
ESEC/SIGSOFT FSE | 1 |