arXiv subjects

Ridewaan Hanslo

Publications and source records attributed to Ridewaan Hanslo.

7 recordsLinked to original sources

arXiv2026

Predicting Agile Success: The Critical Few Factors

While Agile projects are more successful than traditional software development project management approaches, their overall success rate remains relatively low, with a high percentage of projects still deemed challenged or failed. This low project success rate is attributed to projects not being rigorously evaluated against critical success factors (CSF) of Agile projects and contemporary project success criteria. To identify the CSF that contribute to Agile software development project success as perceived by Agile practitioners, this study used a positivist approach to investigate the CSF of Agile software development projects. PLS-SEM with SmartPLS was used to analyse the data and test the hypotheses to identify significant relationships between the constructs and project success criteria. This research found that a few critical factors significantly contribute to Agile project success. The study developed a novel model that can be used to evaluate and measure project success.

cs.SE↗

arXiv2026

A Framework of Critical Success Factors for Agile Software Development

Despite the popularity of Agile software development, achieving consistent project success remains challenging. This systematic literature review identifies critical success factors (CSFs) in Agile projects by analyzing 53 primary studies. Employing thematic synthesis with content analysis, our analysis yielded 21 CSFs categorized into five themes: organizational, people, technical, process, and project. Team effectiveness and project management emerged as the most frequently cited CSFs, highlighting the importance of people and process factors. These interpreted themes and factors contributed to the development of a theoretical framework to identify how these factors contribute to project success. This study offers valuable insights for researchers and practitioners, guiding future research to validate these findings and test the proposed framework using quantitative methods.

cs.SE↗

arXiv2025

Employee Performance when Implementing Agile Practices in an IT Workforce

Adoption of agile practices has increased in IT workforces. However, there is a lack of comprehensive studies in the African context on employee performance when implementing agile practices. This study addresses this gap by exploring employee performance in agile environments for IT workforces in South Africa. An interpretivist mono-method qualitative approach was used, with the use of interviews as a research strategy. Seventeen semi-structured interviews were conducted with agile practitioners from various roles. Our results indicated that agile practices influence employee performance significantly, with participants reporting on aspects which included planning, communication, employee development and well-being, collaboration, team culture and progress. Additionally, our results reported obstacles when using agile practices that included adoption, team engagement, leadership and instilling an agile mindset. Agile practices influence employee performance in IT workforces by fostering improved team dynamics, enhanced collaboration, improved efficiencies, risk management, planning, continuous improvement, learning, personal development and well-being. Conclusively, our findings suggest that if agile challenges are addressed and additional support is provided, employee performance can be significantly improved.

cs.SE↗

arXiv2025

The Evolution of Agile and Hybrid Project Management Methodologies: A Systematic Literature Review

The rapid evolution of IT projects has driven the transformation of project management methodologies, from traditional waterfall approaches to agile frameworks and, more recently, hybrid models. This systematic literature review investigates the evolution of agile methodologies into hybrid frameworks, analysing their implementation challenges and success factors. We identify key trends through PRISMA-guided analysis of peer-reviewed studies from the last 8 years. Hybrid methodologies emerge from agile limitations in large-scale and regulated environments, combining iterative flexibility with structured governance. Agile has several implementation challenges, leading to hybrid methods, and the success hinges on leadership support, tailored process integration, and continuous improvement mechanisms. The study explores the need for contextual adaptation over rigid frameworks, offering practical insights for organisations navigating hybrid transitions.

cs.SE↗

arXiv2025

The Integration of Agile Methodologies in DevOps Practices within the Information Technology Industry

The demand for rapid software delivery in the Information Technology (IT) industry has significantly intensified, emphasising the need for faster software products and service releases with enhanced features to meet customer expectations. Agile methodologies are replacing traditional approaches such as Waterfall, where flexibility, iterative development and adaptation to change are favoured over rigid planning and execution. DevOps, a subsequent evolution from Agile, emphasises collaborative efforts in development and operations teams, focusing on continuous integration and deployment to deliver resilient and high-quality software products and services. This study aims to critically assess both Agile and DevOps practices in the IT industry to identify the feasibility and applicability of Agile methods in DevOps practices. Eleven semi-structured interviews were conducted with Agile and DevOps practitioners in varying capacities across several sectors within the IT industry. Through thematic analysis, 51 unique codes were extracted and synthesised into 19 themes that reported on each phase of the DevOps lifecycle, specifically regarding the integration and implementation of Agile methods into DevOps practices. Based on the findings, a new understanding detailing the interrelationship of Agile methods in DevOps practices was discussed that met the research objectives.

cs.SE↗

arXiv2022

Factors that Contribute to the Success of a Software Organisation's DevOps Environment: A Systematic Review

This research assesses the aspects of software organizations' DevOps environments and identifies the factors contributing to these environments' success. DevOps is a recent concept, and many organizations are moving from old-style software development methods to agile approaches such as DevOps. However, there is no comprehensive information on what factors impact the success of the DevOps environment once organizations adopt it. This research focused on addressing this gap through a systematic literature review. The systematic review consisted of 33 articles from five selected search systems and databases from 2015 to 2021. Based on the included articles, 15 factors were identified and grouped into four categories: Collaborative Culture, Organizational Aspects, Tooling and Technology, and Continuous Practices. In addition, this research proposes a DevOps environment success factors model to potentially contribute to DevOps research and practice. Recommendations are made for additional research on the effectiveness of the proposed model and its success factors.

cs.SE↗

arXiv2022

Deep Learning Transformer Architecture for Named Entity Recognition on Low Resourced Languages: State of the art results

This paper reports on the evaluation of Deep Learning (DL) transformer architecture models for Named-Entity Recognition (NER) on ten low-resourced South African (SA) languages. In addition, these DL transformer models were compared to other Neural Network and Machine Learning (ML) NER models. The findings show that transformer models substantially improve performance when applying discrete fine-tuning parameters per language. Furthermore, fine-tuned transformer models outperform other neural network and machine learning models on NER with the low-resourced SA languages. For example, the transformer models obtained the highest F-scores for six of the ten SA languages and the highest average F-score surpassing the Conditional Random Fields ML model. Practical implications include developing high-performance NER capability with less effort and resource costs, potentially improving downstream NLP tasks such as Machine Translation (MT). Therefore, the application of DL transformer architecture models for NLP NER sequence tagging tasks on low-resourced SA languages is viable. Additional research could evaluate the more recent transformer architecture models on other Natural Language Processing tasks and applications, such as Phrase chunking, MT, and Part-of-Speech tagging.

cs.CL↗