Bibliographic record
Abstract
Recently, there has been an interest in finding ways to combine reuse and customization as practiced in software product line engineering with concepts like iterative development and minimalism as preached by agile methods.This special issue presents cutting-edge research in the area of agile product line engineering.For the past few decades, the software community has put forward numerous efforts to lower the cost of software development, shorten the time-to-market of software products, and improve quality.Software product line engineering is one paradigm that aims to achieve these goals by means of systematic reuse and customization.In a software product line, similar software systems in a given domain are built using a library of core assets (typically developed in a phase called domain engineering).These assets can then be tailored to satisfy customer-specific needs (typically in a phase called application engineering).Another popular approach to achieve rapid delivery of software with minimal overhead is agile software development.Agile development promotes fast delivery of working software over a series of iterations, and it preaches concepts of simplicity and minimalism to cut waste (e.g.lengthy documentation, extensive modeling, and process definitions).Recently, there has been an interest in finding synergies between software product line engineering and agile software development in order to amplify production capabilities even further.This special issue presents the recent research in this direction.For this special issue, a call for papers was announced during the second XP workshop on agile product line engineering.The workshop was co-located with the 11th International Conference on Agile Software Development (XP2010) in Norway.Six submissions were received.For each submission, reviews were solicited from at least two independent reviewers.After two rounds of reviews, four articles were selected to be included in this issue.Two of the articles describe case studies conducted in software companies, while the other two are systematic reviews with different foci.The article by Jan Bosch and Petra M. Bosch-Sijtsema 'Introducing agile customer-centered development in a legacy software product line' discusses software product lines and agile methods in light of the issues associated with large-scale software development such as high coordination overhead, slow release cycles, and increasing error density.The authors present a case study of a Fortune 1000 company that delivers mostly finance and accounting software solutions.The company owns a product line that is the market leader in its domain in the U.S. with a market share of around 75%.In the article, the authors report on 14 semi-structured interviews that were conducted in the company to collect data on the challenges the company had faced with their original product line approach.The interviews covered discussions on the old and the new processes and the change towards the new process.The interviews along with other collected data were systematically coded, labeled and categorized over a number of iterations.The data revealed four main challenges, namely: the lack of customer feedback, heavyweight processes, inefficient utilization of resources, and low engagement of team members.The authors proposed a new approach to address these challenges.The approach used elements from design thinking, agile software development, and self-organizing teams.The results of adopting the new approach demonstrated improved customer involvement throughout the development process, reduced process overhead through the transition from component teams to feature teams, more efficient use of resources by enabling personnel to work in parallel, and increased team autonomy and motivation.Geir K. Hanssen's article 'Agile Software Product Line Engineering: Enabling Factors' reports the results of an extensive industrial case study to identify and understand enabling factors
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.252 | 0.133 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".