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20202026
most citedImpact on the Productivity of Remotely Working IT Professionals of Bangladesh during the Coronavirus Disease 2019

4 citations · 4 across the 7 of their papers we have counts for

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7 papers · 1 filter

cs.SE2026

Which Optimizer, At What Budget? A Tournament of Optimizers for Search-Based SE

Kishan Kumar Ganguly, Tim Menzies

Configuring and tuning modern software is unavoidable, expensive, and error-prone: a single system can expose hundreds of interacting options, and scoring one setting can mean a fu…

cs.SE2026

Zoom, Don't Wander: Why Regional Search Outperforms Pareto Reasoning and Global Optimization in Budget-Constrained SBSE

Kishan Kumar Ganguly, Tim Menzies

Traditional Search-Based Software Engineering (SBSE) assumes global search and full Pareto exploration are essential. We offer the following negative result based on a study of ove…

cs.SE2026

From Verification to Herding: Exploiting Software's Sparsity of Influence

Tim Menzies, Kishan Kumar Ganguly

Software verification is now costly, taking over half the project effort while failing on modern complex systems. We hence propose a shift from verification and modeling to herding…

cs.SE2025

From Coverage to Causes: Data-Centric Fuzzing for JavaScript Engines

Kishan Kumar Ganguly, Tim Menzies

Context: Exhaustive fuzzing of modern JavaScript engines is infeasible due to the vast number of program states and execution paths. Coverage-guided fuzzers waste effort on low-ris…

cs.SE2025

How Low Can You Go? The Data-Light SE Challenge

Kishan Kumar Ganguly, Tim Menzies

Much of Software Engineering (SE) research assumes that progress depends on massive datasets and CPU-intensive optimizers. Yet has this assumption been rigorously tested? The count…

cs.SE2025

MOOT: a Repository of Many Multi-Objective Optimization Tasks

Tim Menzies, Tao Chen, Yulong Ye +4

Software engineers must make decisions that trade off competing goals (faster vs. cheaper, secure vs. usable, accurate vs. interpretable, etc.). Despite MSR's proven techniques for…

cs.SE2025

BINGO! Simple Optimizers Win Big if Problems Collapse to a Few Buckets

Kishan Kumar Ganguly, Tim Menzies

Traditional multi-objective optimization in software engineering (SE) can be slow and complex. This paper introduces the BINGO effect: a novel phenomenon where SE data surprisingly…