Demo Data from SIGIR 2026 / reviewers in the wild / expert
Kushal Ahmed
dblp:140/7498
· DBLP profile ↗
2ranked-venue papers
2as first author
0since 2021 · last 2015
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 2 · 2 first-author
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 |
Requirements engineering and software design · 100% | |
| Theoretical computer science
1 paper |
Logic in computer science · 50% Computational complexity · 50% |
Topics — the 4 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Requirements engineering and software design
formal specification |
0.2 | 1 | 2014 | Formalisation of the integration of behavior trees · ASE 2014 |
Requirements engineering and software design
requirements modeling |
0.2 | 1 | 2014 | Formalisation of the integration of behavior trees · ASE 2014 |
Computational complexity
constraint satisfaction |
0.1 | 1 | 2014 | Formalisation of the integration of behavior trees · ASE 2014 |
Logic in computer science
process algebra |
0.1 | 1 | 2014 | Formalisation of the integration of behavior trees · ASE 2014 |
Methods — techniques the papers use, named apart from their topics
semantic network model · 0.4communicating sequential processes · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2015 | Semantic Network Model: A Reasoning Engine for Software RequirementsabstractIn this paper, we present a semantic network model (SNM) as a reasoning engine for the requirements models. The SNM consists of the vertices and the edges, in which they store information of the models and their interrelations. The SNM, through a semi-automated normalisation process, helps the user (1) to assign states to the models and their relations as to whether they can be included, excluded, or undecided, (2) to eliminate redundant interrelations, (3) to avoid over-specification, and (4) to visualise a simplified overview of the whole system. Finally, we formulate the well-formedness of the SNM, which indicates whether the given models can produce a formal specification. We also evaluate our techniques using several case studies. Kushal Ahmed, Lian Wen, Abdul Sattar 0001, Reza Farid |
ICECCS | 1 |
| 2014 | Formalisation of the integration of behavior treesabstractIn this paper, we present a formal definition of the integration of the requirements modeling language Behavior Trees (BTs). We first provide the semantic integration of two interrelated BTs using an extended version of Communicating Sequential Processes. We then use a Semantic Network Model to capture a set of interrelated BTs, and develop algorithm to integrate them all into one BT. This formalisation facilitates developing (semi-)automated tools for modeling the requirements of large-scale software intensive systems. Kushal Ahmed, M. A. Hakim Newton, Lian Wen, Abdul Sattar 0001 |
ASE | 1 |