Software engineering at the speed of light: how developers stay current using twitter

Singer, Leif; Filho, Fernando Figueira; Storey, Margaret-Anne

doi:10.1145/2568225.2568305

Cited by 110 publications

(68 citation statements)

References 19 publications

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“…Given the exploratory nature of this study subject and our research questions, we decided on a mixed-method study protocol that combines qualitative and exploratory elements with a structured, quantitative survey.This follows the recommendations by Bratthall and Jørgensen [8] as well as established practice used in other, comparable studies in software engineering [9,10,2].…”

Section: Methodsmentioning

confidence: 77%

A mixed-method empirical study of Function-as-a-Service software development in industrial practice

Leitner

Wittern

Spillner

et al. 2018

Preprint

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Function-as-a-Service (FaaS) describes cloud computing services that make infrastructure components transparent to application developers, thus falling in the larger group of "serverless" computing models. When using FaaS offerings, such as AWS Lambda, developers provide atomic and short-running code for their functions, and FaaS providers execute and horizontally scale them on-demand. Currently, there is no systematic research on how developers use serverless, what types of applications lend themselves to this model, or what architectural styles and practices FaaS-based applications are based on. We present results from a mixed-method study, combining interviews with advanced practitioners, a systematic analysis of grey literature, and a Web-based survey. We find that successfully adopting FaaS requires a different mental model, where systems are primarily constructed by composing pre-existing services, with FaaS often acting as the "glue" that brings these services together. Tooling availability and maturity, especially related to testing and deployment, remains a major difficulty. Further, we find that current FaaS systems lack systematic support for function reuse, and abstractions and programming models for building non-trivial FaaS applications are limited. We conclude with a discussion of implications for FaaS providers, software developers, and researchers.

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Section: Methodsmentioning

confidence: 77%

A mixed-method empirical study of Function-as-a-Service software development in industrial practice

Leitner

Wittern

Spillner

et al. 2018

Preprint

View full text Add to dashboard Cite

show abstract

“…Due to the large amount of data extracted from our review process, we established 5 as a threshold for the minimum number of repetitions of a pattern required for it to be considered a theme [27]. This heuristic is based on the assumption that if more users are supporting a specific theme then it is likely to be stronger and more useful.…”

Section: Methodsmentioning

confidence: 99%

Mining questions about software energy consumption

Pinto

Castor

Liu

2014

Proceedings of the 11th Working Conference on Mining Software Repositories

166

122

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A growing number of software solutions have been proposed to address application-level energy consumption problems in the last few years. However, little is known about how much software developers are concerned about energy consumption, what aspects of energy consumption they consider important, and what solutions they have in mind for improving energy efficiency. In this paper we present the first empirical study on understanding the views of application programmers on software energy consumption problems. Using StackOverflow as our primary data source, we analyze a carefully curated sample of more than 300 questions and 550 answers from more than 800 users. With this data, we observed a number of interesting findings. Our study shows that practitioners are aware of the energy consumption problems: the questions they ask are not only diverse -we found 5 main themes of questions -but also often more interesting and challenging when compared to the control question set. Even though energy consumption-related questions are popular when considering a number of different popularity measures, the same cannot be said about the quality of their answers. In addition, we observed that some of these answers are often flawed or vague. We contrast the advice provided by these answers with the state-of-the-art research on energy consumption. Our summary of software energy consumption problems may help researchers focus on what matters the most to software developers and end users.

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“…Previous work investigated the automatic processing of tweets mentioning programming languages, e.g., [19], [20]. Singer et al [21] interviewed and surveyed developers on their Twitter use. Their results describe developers' information overload and their difficulties in obtaining technical information.…”

Section: Related Workmentioning

confidence: 99%

A Little Bird Told Me: Mining Tweets for Requirements and Software Evolution

Guzmán

Ibrahim

Glinz

2017

2017 IEEE 25th International Requirements Engineering Conference (RE)

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Abstract-Twitter is one of the most popular social networks. Previous research found that users employ Twitter to communicate about software applications via short messages, commonly referred to as tweets, and that these tweets can be useful for requirements engineering and software evolution. However, due to their large number-in the range of thousands per day for popular applications-a manual analysis is unfeasible.In this work we present ALERTme, an approach to automatically classify, group and rank tweets about software applications. We apply machine learning techniques for automatically classifying tweets requesting improvements, topic modeling for grouping semantically related tweets and a weighted function for ranking tweets according to specific attributes, such as content category, sentiment and number of retweets. We ran our approach on 68,108 collected tweets from three software applications and compared its results against software practitioners' judgement. Our results show that ALERTme is an effective approach for filtering, summarizing and ranking tweets about software applications. ALERTme enables the exploitation of Twitter as a feedback channel for information relevant to software evolution, including end-user requirements.

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Software engineering at the speed of light: how developers stay current using twitter

Cited by 110 publications

References 19 publications

A mixed-method empirical study of Function-as-a-Service software development in industrial practice

A mixed-method empirical study of Function-as-a-Service software development in industrial practice

Mining questions about software energy consumption

A Little Bird Told Me: Mining Tweets for Requirements and Software Evolution

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