Impact of Programming Language Fragmentation on Developer Productivity

Krein, Jonathan L.; MacLean, Alexander; Knutson, Charles D.; Delorey, Daniel P.; Eggett, Dennis L.

doi:10.4018/jossp.2010040104

Cited by 16 publications

(7 citation statements)

References 18 publications

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“…This data set has been previously used in a number of studies [6,7,8,13,14,15,16]. The logs for all projects in our data set were extracted from the CVS version control system.…”

Section: Methodsmentioning

confidence: 99%

Cliff Walls: An Analysis of Monolithic Commits Using Latent Dirichlet Allocation

Pratt

MacLean

Knutson

et al. 2011

IFIP Advances in Information and Communication Technology

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Abstract. Artifact-based research provides a mechanism whereby researchers may study the creation of software yet avoid many of the difficulties of direct observation and experimentation. However, there are still many challenges that can affect the quality of artifact-based studies, especially those studies examining software evolution. Large commits, which we refer to as "Cliff Walls," are one significant threat to studies of software evolution because they do not appear to represent incremental development. We used Latent Dirichlet Allocation to extract topics from over 2 million commit log messages, taken from 10,000 SourceForge projects. The topics generated through this method were then analyzed to determine the causes of over 9,000 of the largest commits. We found that branch merges, code imports, and auto-generated documentation were significant causes of large commits. We also found that corrective maintenance tasks, such as bug fixes, did not play a significant role in the creation of large commits.

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“…This data set has been previously used in a number of studies [6,7,8,13,14,15,16]. The logs for all projects in our data set were extracted from the CVS version control system.…”

Section: Methodsmentioning

confidence: 99%

Cliff Walls: An Analysis of Monolithic Commits Using Latent Dirichlet Allocation

Pratt

MacLean

Knutson

et al. 2011

IFIP Advances in Information and Communication Technology

Self Cite

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“…Although our evaluation briefly tackles productivity, in this section we aim only to show that SWITCH IDE is capable of supporting software development of cloud-native applications with co-programming efficiently throughout their entire life-cycle. On the other hand, more evaluation, on real-world tasks and with control groups, would be needed in order to prove that productivity is improved by using SWITCH [38]. Most of productivity measurements focus on Lines of Code, which cannot be used in our case, as SIDE is closely related to graphic programming languages [39].…”

Section: Discussionmentioning

confidence: 99%

SWITCH workbench: A novel approach for the development and deployment of time-critical microservice-based cloud-native applications

Štefanič

Cigale

Jones

et al. 2019

Future Generation Computer Systems

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Time-critical applications, such as early warning systems or live event broadcasting, present particular challenges. They have hard limits on Quality of Service constraints that must be maintained, despite network fluctuations and varying peaks of load. Consequently, such applications must adapt elastically on-demand, and so must be capable of reconfiguring themselves, along with the underlying cloud infrastructure, to satisfy their constraints. Software engineering tools and methodologies currently do not support such a paradigm. In this paper, we describe a framework that has been designed to meet these objectives, as part of the EU SWITCH project. SWITCH offers a flexible co-programming architecture that provides an abstraction layer and an underlying infrastructure environment, which can help to both specify and support the life cycle of time-critical cloud native applications. We describe the architecture, design and implementation of the SWITCH components and describe how such tools are applied to three time-critical real-world use cases.

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“…Programming languages vary greatly in the number of lines of code required to produce the same results [2], [3], [4], [6], [7]. For example, consider the difference in terseness between C and Perl.…”

Section: B Programming Language Verbositymentioning

confidence: 99%

Apache commits: Social network dataset

MacLean

Knutson

2013

2013 10th Working Conference on Mining Software Repositories (MSR)

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Building non-trivial software is a social endeavor. Therefore, understanding the social network of developers is key to the study of software development organizations. We present a graph representation of the commit behavior of developers within the Apache Software Foundation for 2010 and 2011. Relationships between developers in the network represent collaborative commit behavior. Several similarity and summary metrics have been pre-calculated. The data, along with the tools that were used to create it and some further discussion, can be found at:

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Impact of Programming Language Fragmentation on Developer Productivity

Cited by 16 publications

References 18 publications

Cliff Walls: An Analysis of Monolithic Commits Using Latent Dirichlet Allocation

Cliff Walls: An Analysis of Monolithic Commits Using Latent Dirichlet Allocation

SWITCH workbench: A novel approach for the development and deployment of time-critical microservice-based cloud-native applications

Apache commits: Social network dataset

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