Intention-Based Integration of Software Variants

Lillack, Max; Stănciulescu, Ștefan; Hedman, Wilhelm; Berger, Thorsten; Wąsowski, Andrzej

doi:10.1109/icse.2019.00090

Cited by 15 publications

(8 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Whereas previous work typically looked at only a small number of hard forks, and research on tooling around hard-fork issues typically focus on few well known projects, such as the variants of BSD [35] or Marlin [28] or artificial or academic variants [14,22], we have detected a significant number of hard forks, many of them recent, using many different languages, that are a rich pool for future research. We release the dataset of all hard forks with corresponding visualizations as dataset with this paper [2].…”

Section: Frequency Of Hard Forksmentioning

confidence: 89%

How has forking changed in the last 20 years?

Zhou

Vasilescu

Kästner

2020

Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering

View full text Add to dashboard Cite

The notion of forking has changed with the rise of distributed version control systems and social coding environments, like GitHub. Traditionally forking refers to splitting off an independent development branch (which we call hard forks); research on hard forks, conducted mostly in pre-GitHub days showed that hard forks were often seen critical as they may fragment a community. Today, in social coding environments, open-source developers are encouraged to fork a project in order to contribute to the community (which we call social forks), which may have also influenced perceptions and practices around hard forks. To revisit hard forks, we identify, study, and classify 15,306 hard forks on GitHub and interview 18 owners of hard forks or forked repositories. We find that, among others, hard forks often evolve out of social forks rather than being planned deliberately and that perception about hard forks have indeed changed dramatically, seeing them often as a positive noncompetitive alternative to the original project.

show abstract

Section: Frequency Of Hard Forksmentioning

confidence: 89%

How has forking changed in the last 20 years?

Zhou

Vasilescu

Kästner

2020

Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering

View full text Add to dashboard Cite

show abstract

“…(2.) The asset is not contained in the target, but needs to be integrated [18] with its siblings in the target, that might not exist beneath its parent in the source. This process is typically difficult to solve automatically, as code can not only be integrated in multiple ways, but in multiple dimensions: in variation points and in ordering.…”

Section: Operationsmentioning

confidence: 99%

“…The evolution is documented by meta-data, usable as ground truth for evaluations. This synthetic version history can be used to benchmark tools that require such a version history as an input, such as feature identification and location [7,28], re-engineering [2] and code integration tools [18]. Our design addresses requirements related to evolving systems in a feature-oriented way, whilst documenting it as meta-data, assuring compilability, and being language-independent and extensible.…”

Section: Introductionmentioning

confidence: 99%

A Generator Framework For Evolving Variant-Rich Software

Derks¹,

Strüber²,

Berger³

2021

Preprint

Self Cite

View full text Add to dashboard Cite

Evolving software is challenging, even more when it exists in many different variants. Such software evolves not only in time, but also in space-another dimension of complexity. While evolution in space is supported by a variety of product-line and variability management tools, many of which originating from research, their level of evaluation varies significantly, which threatens their relevance for practitioners and future research. Many tools have only been evaluated on ad hoc datasets, minimal examples or available preprocessor-based product lines, missing the early clone & own phases and the re-engineering into configurable platforms-large parts of the actual evolution lifecycle of variant-rich systems. Our long-term goal is to provide benchmarks to increase the maturity of evaluating such tools. However, providing manually curated benchmarks that cover the whole evolution lifecycle and that are detailed enough to serve as ground truths, is challenging.We present the framework vpbench to generates source-code histories of variant-rich systems. Vpbench comprises several modular generators relying on evolution operators that systematically and automatically evolve real codebases and document the evolution in detail. We provide simple and more advanced generators-e.g., relying on code transplantation techniques to obtain whole features from external, real-world projects. We define requirements and demonstrate how vpbench addresses them for the generated version histories, focusing on support for evolution in time and space, the generation of detailed meta-data about the evolution, also considering compileability and extensibility. CCS CONCEPTS• Software and its engineering → Software product lines.

show abstract

“…Furthermore, most of our use cases applying clone & own also have an integrated platform, that is, a project with common assets. We are only aware of one work in this direction (Lillack et al 2019), which should further be complemented with methodologies and tools.…”

Section: Limitations Of Clone-management Techniquesmentioning

confidence: 99%

“…Specifically, as pointed out for our railway case, there should be means to express historical additions, suppressions, and modifications at the highest level of abstraction, specifically distinguishing architectural and functional evolutions. As such, practically usable, dedicated diffing techniques, which support existing variation points (e.g., #ifdef), are needed, potentially building upon recent techniques such as intention-based clone integration (Lillack et al 2019). Enhanced visualization capabilities should also support highly scattered features (Passos et al 2015(Passos et al , 2018, as explained for the web application and power electronics case.…”

Section: Diffing Of Cloned Variantsmentioning

confidence: 99%

The state of adoption and the challenges of systematic variability management in industry

et al. 2020

Self Cite

View full text Add to dashboard Cite

Handling large-scale software variability is still a challenge for many organizations. After decades of research on variability management concepts, many industrial organizations have introduced techniques known from research, but still lament that pure textbook approaches are not applicable or efficient. For instance, software product line engineering-an approach to systematically develop portfolios of products-is difficult to adopt given the high upfront investments; and even when adopted, organizations are challenged by evolving their complex product lines. Consequently, the research community now mainly focuses on reengineering and evolution techniques for product lines; yet, understanding the current state of adoption and the industrial challenges for organizations is necessary to conceive effective techniques. In this multiple-case study, we analyze the current adoption of variability management techniques in twelve medium-to large-scale industrial cases in domains such as automotive, aerospace or railway systems. We identify the current state of variability management, emphasizing the techniques and concepts they adopted. We elicit the needs and challenges expressed for these cases, triangulated with results from a literature review. We believe our results help to understand the current state of adoption and shed light on gaps to address in industrial practice.

show abstract

Intention-Based Integration of Software Variants

Cited by 15 publications

References 32 publications

How has forking changed in the last 20 years?

How has forking changed in the last 20 years?

A Generator Framework For Evolving Variant-Rich Software

The state of adoption and the challenges of systematic variability management in industry

Contact Info

Product

Resources

About