Paper Info
Title
Investigating the Impact of Experience and Solo/Pair Programming on Coding Efficiency: Results and Experiences from Coding Contests.
Abstract
Developing working software is a key goal of software development. Beyond software processes, following traditional or agile approaches, coding strategies, i.e., solo and pair programming, are important aspects for constructing high quality software code. In addition developer experience has a critical impact on coding efficiency and code quality. Pair programming aims at increasing coding efficiency, code quality, and supports learning of development team members. Several controlled experiments have been conducted to investigate benefits of different development strategies, learning effects, and the impact on code quality in academia and industry. Nevertheless, reported study limitations and various results in different contexts require more studies to fully understand the effects of experience and programming strategies. Coding contests can be promising approaches to (a) involve different participant groups, e.g., junior and senior programmers and professionals, and (b) can represent a well-defined foundation for planning and executing largescale empirical studies. In this paper we present coding contests as a promising strategy for conducting empirical studies with heterogeneous groups of participants and report on a set of findings from past coding contests. Main results are (a) that the concept of coding contests is a promising way for supporting empirical research and (b) the results partly confirm previous studies that report on the benefits of pair programming and development experience.
Year
DOI
Venue
2013
10.1007/978-3-642-38314-4_8
AGILE PROCESSES IN SOFTWARE ENGINEERING AND EXTREME PROGRAMMING, XP 2013
Keywords
Field
DocType
Coding Contests,Large Scale Controlled Experiments,Solo Programming,Pair Programming,Developer Experience
Learning effect,Pair programming,Software engineering,Simulation,Coding (social sciences),Agile software development,Software,Engineering,Software quality,Software development,Empirical research
Conference
Volume
ISSN
Citations 
149
1865-1348
0
PageRank 
References 
Authors
0.34
12
4
Name
Order
Citations
PageRank
Dietmar Winkler1828.81
Martin Kitzler200.34
Christoph Steindl3304.55
Stefan Biffl41305134.26