arXiv subjects

Mohit Kaushik

Publications and source records attributed to Mohit Kaushik.

5 recordsLinked to original sources

arXiv2026

Removing Noise or Introducing Bias? The Hidden Cost of MSR Filtering

OSS platforms like GitHub serve as a primary data source for MSR research. As the platform is widely used by different users, spanning from student to developer, not all repositories are actual engineered projects. Therefore, to avoid such noise, researchers often apply several criteria, which may fundamentally change the sample demographics. To understand such biases, this study aims to uncover the hidden cost originating from these arbitrary thresholds or criteria. We analyzed 1.57 million repositories from the SEART platform and constructed several datasets from the thresholds often applied in MSR research. We identify the maintenance bias in these filtering processes, which masks the true abandonment (73.42%) realities of OSS projects. Also, these strategies favor some ecosystems and governance styles. Moreover, the sampling strategy also distorts the relationship between variables, suffering from relational biases. Therefore, to avoid such biases, the researchers should shift towards stratified sampling and refining the criteria for noise detection.

cs.SE↗

arXiv2026

Social Popularity of GitHub Projects: A Lifeline or a Liability?

Social coding platforms such as GitHub host millions of repositories, yet many suffer from high mortality rates. Despite this, several survival factors remain poorly understood. Human capital is widely recognized as essential. Social attention, while often assumed to be a lifeline, can become a liability. Structural features that improve onboarding, such as code readability and documentation, may also accelerate the cessation of active development when combined with massive visibility. To examine these dynamics, we analyzed more than 73,000 GitHub repositories using an Accelerated Failure Time (AFT) survival framework, which accounts for the time-varying nature of predictors. Our study identifies human capital as the most critical determinant of project survival. In contrast, excessive social attention emerges as a liability, and when coupled with accessibility features, it amplifies the risk of project inactivity. Importantly, when the number of contributors interacts with social popularity, the protective effect of labor becomes visible, highlighting the need for governance strategies that balance visibility with labor capacity to ensure the long-term resilience of open-source projects.

cs.SE↗

arXiv2026

CloudyGUI: A Novel Python-based Framework for Auto-Scaling and Cloud Workload Analysis

Purpose: Cloud computing environments are highly dynamic, creating major challenges for resource management. Accurate workload prediction is therefore essential for effective auto-scaling. To address this, we present CloudyGUI, a Python simulation framework with an easy-to-use GUI that allows researchers to test and validate resource management strategies. Methods: This framework employs a three-stage pipeline: workload generation, prediction (utilizing XGBoost and LSTM), and an auto-scaling system based on the MAPE loop. Validation includes internal, intermediate, and external methods to ensure system reliability. Results: CloudyGUI's generated workloads closely match real-world datasets. A two-sample K-S test confirms this alignment, showing strong p-values of 0.19 for CPU and 0.14 for memory. When compared to a command-line tool, the GUI adds only a minimal overhead of 1.4x-4.67x. Furthermore, expert review validates the tool's realism and practical usefulness. Conclusion: CloudyGUI fills a critical gap by providing an accessible and efficient platform for simulating auto-scaling in cloud applications, helping researchers develop advanced cloud management solutions.

cs.DC↗

arXiv2026

The Death Spiral of Open Source Projects: A Post-Mortem Analysis of Pull Request Workflow Dynamics

Open Source Software projects (OSS) are central to modern technology, yet their survival rates remain low. Prior research has examined project mortality through macro-level indicators such as commit activity, developer abandonment, and ecosystem dependencies, but the micro-level dynamics of the Pull Request (PR) workflow have been largely overlooked. This study provides the first large-scale post-mortem analysis of PR workflows across 1,736 inactive GitHub repositories and 1.3 million human-driven PRs. Using a mixed-method quantitative design, we investigate three dimensions of mortality. First, our comparative descriptive analysis shows that workflow friction, extended review cycles, and negativity penalties are endemic properties of the entire GitHub platform across both active and inactive projects. Rejected PRs consistently attract higher discussion and negativity regardless of project health. Second, our evolutionary analysis identifies a universal ``death spiral" marked by declining innovation rates, exponential backlog growth, rising merge latency. The collapse was defined by silence and disengagement. Labeling formalization remained endemic throughout the lifecycle, while toxicity did not intensify. Finally, our explanatory modeling demonstrates that project lifespan is not determined by workflow efficiency but by inherent value and ecosystem dynamics. Popularity and innovation emerge as strong positive predictors of survival, while friction, rejection rates, labeling formalization, and negativity scale with longevity as byproducts rather than causes of failure. Robustness checks across alternative inactivity thresholds confirm these findings. Together, this work reframes OSS mortality as a socio-technical phenomenon in which abandonment and ecosystem value dominate survival outcomes, while PR-level workflow discipline plays a secondary role.

cs.SE↗

arXiv2026

Community Engagement and the Lifespan of Open-Source Software Projects

Open-source software (OSS) projects depend on community engagement (CE) for longevity. However, CE's quantifiable impact on project dynamics and lifespan is underexplored. Objectives: This study defines CE in OSS, identifies key metrics, and evaluates their influence on project dynamics (releases, commits, branches) and lifespan. Methods: We analyzed 33,946 GitHub repositories, defining and operationalizing CE with validated per-month metrics (issues, comments, watchers, stargazers). Non-parametric tests and correlations assessed relationships with project dynamics and lifespan across quartiles. Results: CE metrics significantly associate with project dynamics, with stronger correlations in highly engaged projects. For lifespan, a complex pattern emerged: per-month CE rates are highest in younger projects, declining with age. Yet, a subset of long-lived projects maintains exceptionally high activity. Initial CE bursts appear crucial for establishment, while sustained high engagement drives extreme longevity. Active issue engagement's influence intensifies with age, but passive attention's declines. Conclusion: CE dynamically drives OSS project longevity and development. Our findings establish validated CE metrics and offer deeper insights into how diverse community activity patterns contribute to project longevity.

cs.SE↗