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53rd Southern African Computer Lecturers Association Meeting

作者： Liebenberg, Janet North West Univ Sch Comp Sci & Informat Syst Potchefstroom South Africa

ISBN: (纸本)9783031824777;9783031824784

It's concerning that in a country where the majority of the population comprises Black South Africans, they constitute the minority within the IT industry. Additionally, the issue of gender inequality persists in IT, with females remaining underrepresented both in IT classes and in the workplace. The aim of this study was to examine the impact that pair programming has on shaping the experiences and perceptions of underrepresented minority students in Information Technology (IT) in South Africa. The study included a total of 284 first-year students taking a User Interface programming module. The students were given the opportunity to pick a desired programming partner and for the duration of the semester, they programmed in pairs. At the end of the semester, the students completed a questionnaire. The findings suggested that the group of students had a positive experience with pair programming. However, the underrepresented minority students had an even more positive learning experience with pair programming. The female students (White and Black) and male Black students perceived pair programming in an exceedingly positive light, as it improved their overall programming skills and teamwork skills. It can be recommended that with timely training and adequate implementation of the pair programming principles, all students, but indeed more so the underrepresented minority students in a programming course can reap the benefits of the use of pair programming. This approach may attract and increase the retention rate of underrepresented groups in IT and encourage them to further pursue IT careers in South Africa.

关键词： pair programming Information Technology Underrepresentation Minorities

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Blockchain-Driven Research in Personality-Based Distributed pair programming 5

Blockchain-Driven Research in Personality-Based Distributed ...

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5th Asia Conference on Information Engineering, ACIE 2025

作者： Valovy, Marcel Buchalcevova, Alena Prague University of Economics and Business Department of Information Technologies Prague Czech Republic

ISBN: (纸本)9798331528409

This study aims to integrate blockchain technology into personality-based pair programming research to enhance its generalizability and adaptability by offering built-in continuous, reproducible, and transparent research. In the developing Role-Optimization Motivation Alignment (ROMA) framework, human/AI programming roles align with individual Big Five personality traits, optimizing individual motivation and team productivity in Very Small Entities and undergraduate courses. Twelve quasi-experimental sessions were conducted to verify the personality-based pair programming in distributed settings. A mixed-methods approach was employed, combining intrinsic motivation inventories and qualitative insights. Data were stored transparently on the Solana blockchain, and a web-based application was developed in Rust and TypeScript languages to facilitate partner matching based on ROMA suggestions, expertise, and availability. The results suggest that blockchain can enhance research generalizability, reproducibility, and transparency, while ROMA can increase individual motivation and team performance. Future work can focus on integrating smart contracts for transparent and versioned data analysis. © 2025 IEEE.

关键词： blockchain intrinsic motivation pair programming personality traits role optimization software engineering Solana

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pair programming in software development teams - An empirical study of its benefits

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INFORMATION AND SOFTWARE TECHNOLOGY 2008年第3期50卷 231-240页

作者： Bipp, Tanja Lepper, Andreas Schmedding, Doris Univ Dortmund Dept Comp Sci D-4600 Dortmund Germany Univ Dortmund Organizat Psychol D-4600 Dortmund Germany

We present the results of an extensive and substantial case study on pair programming, which was carried out in courses for software development at the University of Dortmund, Germany. Thirteen software development teams with about 100 students took part in the experiments. The groups were divided into two sets with different working conditions. In one set, the group members worked on their projects in pairs. Even though the paired teams could only use half of the workstations the teams of individual workers could use, the paired teams produced nearly as much code as the teams of individual workers at the same time. In addition, the code produced by the paired teams was easier to read and to understand. This facilitates finding errors and maintenance. (C) 2007 Elsevier B.V. All rights reserved.

关键词： pair programming empirical software engineering quality of software

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pair programming productivity: Novice-novice vs. expert-expert

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INTERNATIONAL JOURNAL OF HUMAN-COMPUTER STUDIES 2006年第9期64卷 915-925页

作者： Lui, Kim Man Chan, Keith C. C. Hong Kong Polytech Univ Dept Comp Hong Kong Hong Kong Peoples R China

Agile Software Development methodologies have grown in popularity both among academic researchers and industrial practitioners. Among the various methodologies or practices proposed, pair programming, which is concerned with two programmers collaborating on design, coding and testing, has become a controversial focus of interest. Even though some success stories have been reported with the use of pair-programming in real software development environment, many people remain rather skeptical of the claims on pair-programming productivity. Previous studies in pair programming have only addressed the basic understanding of the productivity of pairs and they have not addressed the variation in productivity between pairs of varying skills and experience, such as between novice-novice and expert-expert. Statistical productivity measurements reported by different researchers also seem to lead to contradictory conclusions. Until now, the literature has not addressed how those results and experiments were related to each other. In this paper, we propose a controlled experiment called repeat-programming which can facilitate the understanding of relationships between human experience and programming productivity. Repeat-programming can be performed when controversial issues in non-traditional programming methodologies and development productivity need to be investigated into. To illustrate how the proposed empirical experiment can put arguable, divisive problems into perspective, we have examined the productivity in pair programming as a case study. With repeat-programming, we are able to (i) better understand why results of previous pair programming control experiments reached different conclusions as to the productivity of pair programming and (ii) most importantly, present a case in which novice-novice pairs against novice solos are much more productive than expert-expert pairs against expert solos. (c) 2006 Elsevier Ltd. All rights reserved.

关键词： programming model pair programming programmer productivity

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pair programming teams and high-quality knowledge sharing: A comparative study of coopetitive reward structures

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INFORMATION SYSTEMS FRONTIERS 2017年第2期19卷 397-409页

作者： Ghobadi, Shahla Campbell, John Clegg, Stewart Univ Manchester Manchester Business Sch Enterprise Informat Syst Manchester Lancs England Univ Canberra Fac Business Govt & Law Canberra ACT Australia Univ Technol Sch Management Sydney NSW Australia

There has been a growing research interest in understanding knowledge sharing in agile development. Yet, empirical research that sheds light on its underlying practices, such as pair programming, is evolving. This study uses insights from coopetition and software literature to focus inquiry on the relation between coopetitive rewards and high-quality knowledge sharing in pair programming teams. Theoretical hypotheses are developed and validated, suggesting that: 'coopetitive rewards influence high-quality knowledge sharing both directly and over time through their impact on the level of knowledge sharing satisfaction', and, 'the impact of coopetitive rewards on high-quality knowledge sharing is dependent upon task complexity and the history of working under similar reward structure'. This study generates new understanding related to the use of rewards in pair programming teams, and offers a rigorous and replicable seven-step experimental process for simulating coopetitive structures and investigating their role in pair programming and in similar collaborative contexts.

关键词： pair programming Agile development Software team Knowledge sharing Information sharing Rewards Coopetition Competitive reward Cooperation Competition

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pair programming and the mysterious role of the navigator

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INTERNATIONAL JOURNAL OF HUMAN-COMPUTER STUDIES 2008年第7期66卷 519-529页

作者： Bryant, Sallyann Romero, Pablo du Boulay, Benedict IDEAS Laboratory University of Sussex UK

Computer programming is generally understood to be highly challenging and since its inception a wide range of approaches, tools and methodologies have been developed to assist in managing its complexity. Relatively recently the potential benefits of collaborative software development have been formalised in the practice of pair programming. Here we attempt to 'unpick' the pair programming process through the analysis of verbalisations from a number of commercial studies. We focus particularly on the roles of the two programmers and what their key characteristics and behaviours might be. In particular, we dispute two existing claims: (i) that the programmer who is not currently typing in code ("the navigator") is constantly reviewing what is typed and highlighting any errors (i.e. acting as a reviewer) and (ii) that the navigator focuses on a different level of abstraction as a way of ensuring coverage at all necessary levels (i.e. acting as a foreman). We provide an alternative model for these roles ("the tag team") in which the driver and navigator play much more equal roles. We also suggest that a key factor in the success of pair programming may be the associated increase in talk at an intermediate level of abstraction. Published by Elsevier Ltd.

关键词： pair programming verbal protocol analysis extreme programming

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pair programming and Software Defects-A Large, Industrial Case Study

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IEEE TRANSACTIONS ON SOFTWARE ENGINEERING 2013年第7期39卷 930-953页

作者： di Bella, Enrico Fronza, Ilenia Phaphoom, Nattakarn Sillitti, Alberto Succi, Giancarlo Vlasenko, Jelena Univ Genoa Dept Econ & Quantitat Methods I-16126 Genoa Italy Free Univ Bozen Bolzano CASE I-39100 Bolzano Italy

In the last decade, there has been increasing interest in pair programming (PP). However, despite the existing work, there is still a lack of substantial evidence of the effects of PP in industrial environments. To address this issue, we have analyzed the work of a team of 17 industrial developers for 14 months. The team is part of the IT department of a large Italian manufacturing company;it adopts a customized version of extreme programming (XP). We have investigated the effects of PP on software quality in five different scenarios. The results show that PP appears to provide a perceivable but small effect on the reduction of defects in these settings.

关键词： pair programming software defects case study

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pair programming With Generative AI

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IEEE SOFTWARE 2024年第3期41卷 16-18页

作者： Spinellis, Diomidis Athens Univ Econ & Business Dept Management Sci & Technol Athens 10434 Greece Delft Univ Technol Software Analyt Dept Software Technol NL-2600 AA Delft Netherlands

Generative AI based on large-language models is significantly impacting software development through IDE assistants, cloud-based APIs, and interactive chatbots for coding assistance. It excels in generating and translating code and data, navigating APIs, and creating boilerplate content, thereby enhancing productivity. However, it is prone to generating inaccurate information ("hallucinations"), erroneous code, and potentially introducing security vulnerabilities. To counter these risks, employing automated analysis tools, conducting rigorous testing, and maintaining a deep understanding of computer science concepts are essential. While generative AI can substantially aid development tasks it is not a replacement for human expertise, especially in understanding complex software, its requirements, and architecture.

关键词： Generative Adversarial Networks Artificial Intelligence Codes Security Navigation Encoding Large Language Models Analytical Models Fake News Information Integrity Human Factors Chatbots pair programming Software Development Application programming Interface Security Vulnerabilities Open Source Software Coded Based Static Analysis International Organization For Standardization Software Libraries Java Script

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pair programming and the Level of Knowledge in the Formation of pairs

Pair Programming and the Level of Knowledge in the Formation...

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9th World Conference on Information Systems and Technologies (WorldCIST)

作者： Sobral, Sonia Rolland Univ Portucalense REMIT Porto Portugal

ISBN: (纸本)9783030726591;9783030726607

The pandemic situation COVID-19 requires teachers to rethink some of the activities proposed to students since even though they are physically in the same room at the university, they cannot join and must maintain a social distance. The curricular unit of introduction to programming in the first year of computer courses requires several activities: students only learn by doing. One of the activities that has been used a lot in the academic community is pair programming: a single computer for two students working together. In the case that this article reports the pair works sharing a ZOOM room and alternates the position of driver (writes the code) with navigator (one that comments on the code). This article uses the technique of pair programming for writing top-down, algorithm and traces to verify the behavior of variables along the algorithm. If the pair programming technique has had very interesting results in terms of task speed and code quality far superior to programmers alone, there are some doubts about the problem of the constitution pf the groups. In this article we use two opposite strategies: group students with opposite knowledge or group students with similar knowledge. We found that students who prefer this activity are the worst ones (in both strategies) and the best students when grouped with colleagues with similar knowledge.

关键词： pair programming COVID-19 CS1 Work group Algorithms

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pair programming in Perspective: Effects on Persistence, Achievement, and Equity in Computer Science

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JOURNAL OF RESEARCH ON EDUCATIONAL EFFECTIVENESS 2020年第4期13卷 731-758页

作者： Bowman, Nicholas A. Jarratt, Lindsay Culver, K. C. Segre, Alberto M. Univ Iowa Dept Educ Policy & Leadership Studies N491 Lindquist Ctr Iowa City IA 52242 USA Univ Southern Calif Pullias Ctr Higher Educ Los Angeles CA 90007 USA Univ Iowa Dept Comp Sci Iowa City IA 52242 USA

pair programming is a form of collaborative learning in computer science that involves two students working together on a coding project. Previous research has identified mostly positive outcomes from this practice, such as course grades and the quality of the resulting code. pair programming may also facilitate interactions that improve the climate for women and Students of Color, thereby reducing equity gaps in achievement and persistence. However, the existing research findings are inconsistent, which may reflect limitations in research design and/or challenges with implementing pair programming in an ideal manner. The present study sought to provide rigorous evidence through a cluster-randomized trial with 1,530 undergraduates in 96 lab sections across three different introductory computer science courses. Within the full sample, pair programming was unrelated to virtually all outcomes. However, pair programming actually led to poorer outcomes among White students, including grades within the introductory course, attempting or completing subsequent computer science courses, and majoring or minoring in computer science. These negative effects were generally driven by White students whose partners had either low or high levels of prior programming experience.

关键词： pair programming computer science college students undergraduate major collaborative learning

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