Journal of Software-Evolution and Process最新文献

{"title":"","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":48898,"journal":{"name":"Journal of Software-Evolution and Process","volume":"38 4","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148110926","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":48898,"journal":{"name":"Journal of Software-Evolution and Process","volume":"38 4","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148079631","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":48898,"journal":{"name":"Journal of Software-Evolution and Process","volume":"38 4","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148106938","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Agile Coach Role Decoded: What Agile Coaches Deliver Versus What Team Members Experience","authors":"Konstantinos Koumaditis,&nbsp;Philip Harder,&nbsp;Bjarke Stokholm Hestbæk,&nbsp;Maja Due Kadenic,&nbsp;Lasse F. Lui","doi":"10.1002/smr.70107","DOIUrl":"https://doi.org/10.1002/smr.70107","url":null,"abstract":"<p>As organizations increasingly adopt agile methodologies to navigate digital transformation, the role of the agile coach has emerged as a critical yet ambiguously defined element of success. This exploratory study investigates agile coaching from a dual perspective, coaches and team members, to better understand the approaches, tools, and perceptions that shape coaching effectiveness. Drawing on survey data from 301 respondents, the study reveals both alignment and divergence in how coaching roles, success characteristics, accountability, and performance metrics are perceived. While both groups value interpersonal skills and team accountability, team members tend to seek more directive support and tangible outcomes, whereas coaches emphasize facilitation and systemic impact. The findings depict the need for more explicit role definitions, mutual expectation setting, and adaptive coaching strategies. Practical recommendations are proposed to bridge perceptual gaps and enhance coaching relationships. This research contributes to the evolving discourse on agile transformation by offering actionable insights for improving coaching alignment and team performance.</p>","PeriodicalId":48898,"journal":{"name":"Journal of Software-Evolution and Process","volume":"38 4","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/smr.70107","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147683654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Agile Coach Role Decoded: What Agile Coaches Deliver Versus What Team Members Experience","authors":"Konstantinos Koumaditis,&nbsp;Philip Harder,&nbsp;Bjarke Stokholm Hestbæk,&nbsp;Maja Due Kadenic,&nbsp;Lasse F. Lui","doi":"10.1002/smr.70107","DOIUrl":"https://doi.org/10.1002/smr.70107","url":null,"abstract":"<p>As organizations increasingly adopt agile methodologies to navigate digital transformation, the role of the agile coach has emerged as a critical yet ambiguously defined element of success. This exploratory study investigates agile coaching from a dual perspective, coaches and team members, to better understand the approaches, tools, and perceptions that shape coaching effectiveness. Drawing on survey data from 301 respondents, the study reveals both alignment and divergence in how coaching roles, success characteristics, accountability, and performance metrics are perceived. While both groups value interpersonal skills and team accountability, team members tend to seek more directive support and tangible outcomes, whereas coaches emphasize facilitation and systemic impact. The findings depict the need for more explicit role definitions, mutual expectation setting, and adaptive coaching strategies. Practical recommendations are proposed to bridge perceptual gaps and enhance coaching relationships. This research contributes to the evolving discourse on agile transformation by offering actionable insights for improving coaching alignment and team performance.</p>","PeriodicalId":48898,"journal":{"name":"Journal of Software-Evolution and Process","volume":"38 4","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/smr.70107","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147683580","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":48898,"journal":{"name":"Journal of Software-Evolution and Process","volume":"38 4","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148073130","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Software Cost Estimation Using a Hybrid Deep Convolutional LSTM and Optimization Approach","authors":"Nitalaksheswara Rao Kolukula,&nbsp;Jhansi Vazram Bolla,&nbsp;Padma Yenuga,&nbsp;Nagul Shaik,&nbsp;James Stephen Meka","doi":"10.1002/smr.70097","DOIUrl":"https://doi.org/10.1002/smr.70097","url":null,"abstract":"<div>\u0000 \u0000 <p>The importance of such software cost estimation (SCE) is that it can be relied upon in the planning and management of large software projects, especially when one is working in an environment that is dynamic and uncertain. The current models can be difficult to scale and model. In these respects, this paper will recommend a hybrid optimization–based deep convolutional LSTM (HO-DCLSTM) framework for solving an SCE. The proposed system takes the form of a deep learning model of a deep convolution LSTM to enhance cost estimates. The suggested solution combines a profound convolutional LSTM network and parameter refinement based on gazelle and Al-Biruni Earth radius optimization algorithms to increase the prediction accuracy of costs and reduce the computation load and volume. The suggested method generates a better solution, has a low cost of computing, and has the ability to locate the best solution. Three datasets are used to analyze the proposed method's performance based on NASA, COCOMO 81, and KEMERER data. The analysis of the results with these datasets shows that the proposed method has high performance with lower error rates and greater prediction accuracy when compared to other current methods.</p>\u0000 </div>","PeriodicalId":48898,"journal":{"name":"Journal of Software-Evolution and Process","volume":"38 4","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147683543","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Software Cost Estimation Using a Hybrid Deep Convolutional LSTM and Optimization Approach","authors":"Nitalaksheswara Rao Kolukula,&nbsp;Jhansi Vazram Bolla,&nbsp;Padma Yenuga,&nbsp;Nagul Shaik,&nbsp;James Stephen Meka","doi":"10.1002/smr.70097","DOIUrl":"10.1002/smr.70097","url":null,"abstract":"<div>\u0000 \u0000 <p>The importance of such software cost estimation (SCE) is that it can be relied upon in the planning and management of large software projects, especially when one is working in an environment that is dynamic and uncertain. The current models can be difficult to scale and model. In these respects, this paper will recommend a hybrid optimization–based deep convolutional LSTM (HO-DCLSTM) framework for solving an SCE. The proposed system takes the form of a deep learning model of a deep convolution LSTM to enhance cost estimates. The suggested solution combines a profound convolutional LSTM network and parameter refinement based on gazelle and Al-Biruni Earth radius optimization algorithms to increase the prediction accuracy of costs and reduce the computation load and volume. The suggested method generates a better solution, has a low cost of computing, and has the ability to locate the best solution. Three datasets are used to analyze the proposed method's performance based on NASA, COCOMO 81, and KEMERER data. The analysis of the results with these datasets shows that the proposed method has high performance with lower error rates and greater prediction accuracy when compared to other current methods.</p>\u0000 </div>","PeriodicalId":48898,"journal":{"name":"Journal of Software-Evolution and Process","volume":"38 4","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147683542","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Graph Attention-Based Contextual Semantic Correlation Analysis for Software Fault Localization","authors":"Hongdou He,&nbsp;Xiaoming Ma,&nbsp;Huazhi Xu,&nbsp;Guyu Zhao","doi":"10.1002/smr.70103","DOIUrl":"10.1002/smr.70103","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 &lt;p&gt;Although the advanced spectrum-based fault localization techniques introduce graph models to measure the faulty suspiciousness of entities, they still lack effective leverage of the contextual semantics of program units, making it difficult to reveal the complex causal relationships of bugs. Therefore, this paper proposes the &lt;b&gt;C&lt;/b&gt;ontextual &lt;b&gt;S&lt;/b&gt;emantic Coupling &lt;b&gt;C&lt;/b&gt;orrelation Analysis for the Software &lt;b&gt;F&lt;/b&gt;ault &lt;b&gt;L&lt;/b&gt;ocalization (CSCFL), employing semantic embedding and coupling correlation of contextual associations based on contextual embedding and graph attention mechanism. Based on the test coverage graph representation, the pre-trained self-attention embedding model encodes the entity embeddings considering context associations, fully mining the contextual information among program entities to obtain contextual feature representation. CSCFL introduces the graph attention network to learn the context semantic coupling correlation between entities. By analyzing the causal relationships and semantic collaborations that lead to faults, the context semantics analysis module automatically weights and aggregates the influence of contextual entities to generate more accurate fault feature representations, thereby improving localization effectiveness. The experimental results show that, with respect to Top-1, Top-3, and Top-5 metrics, the proposed method outperforms the baseline methods by &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mn&gt;7&lt;/mn&gt;\u0000 &lt;mo&gt;.&lt;/mo&gt;\u0000 &lt;mn&gt;59&lt;/mn&gt;\u0000 &lt;mo&gt;%&lt;/mo&gt;\u0000 &lt;mo&gt;,&lt;/mo&gt;\u0000 &lt;mspace&gt;&lt;/mspace&gt;\u0000 &lt;mn&gt;4&lt;/mn&gt;\u0000 &lt;mo&gt;.&lt;/mo&gt;\u0000 &lt;mn&gt;73&lt;/mn&gt;\u0000 &lt;mo&gt;%&lt;/mo&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt;$$ 7.59%,kern0.3em 4.73% $$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;, and &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mn&gt;1&lt;/mn&gt;\u0000 &lt;mo&gt;.&lt;/mo&gt;\u0000 &lt;mn&gt;41&lt;/mn&gt;\u0000 &lt;mo&gt;%&lt;/mo&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt;$$ 1.41% $$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;, respectively, and outperforms cutting-edge LLM-based methods by &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mn&gt;9&lt;/mn&gt;\u0000 &lt;mo&gt;.&lt;/mo&gt;\u0000 &lt;mn&gt;10&lt;/mn&gt;\u0000 &lt;mo&gt;%&lt;/mo&gt;\u0000 &lt;mo&gt;,&lt;/mo&gt;\u0000 &lt;mspace&gt;&lt;/mspace&gt;\u0000 &lt;mn&gt;13&lt;/mn&gt;\u0000 &lt;mo&gt;.&lt;/mo&gt;\u0000 &lt;mn&gt;71&lt;/mn&gt;\u0000 &lt;mo&gt;%&lt;/mo&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt;$$ 9.10%,kern0.3em 13.71% $$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;, and &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mn&gt;20&lt;/mn&gt;\u0000 &lt;mo&gt;.&lt;/mo&gt;\u0000 &lt;mn&gt;67&lt;/mn&gt;\u0000 &lt;mo&gt;%&lt;/mo&gt;\u0000 &lt;/mro","PeriodicalId":48898,"journal":{"name":"Journal of Software-Evolution and Process","volume":"38 4","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147683631","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Toward Platform Engineering, the Evolution of DevOps—A Systematic Mapping","authors":"Yohan Guisao,&nbsp;Elizabeth Suescún,&nbsp;Paola Noreña,&nbsp;César Pardo","doi":"10.1002/smr.70108","DOIUrl":"10.1002/smr.70108","url":null,"abstract":"<div>\u0000 \u0000 <p>The evolution of software development can be traced parallel to the recent industrial revolutions, which have significantly changed modern society. Recent advancements have transformed how software is created, distributed, and utilized. In the digitalization of industry, software development is created by using innovative solutions for artificial intelligence, machine learning, the Internet of Things, cloud computing, and more. Platform engineering evolves DevOps by integrating development (Dev) and IT operations (Ops) for enhancing developer experience and accelerating customer value delivery. This paper maps the current landscape of platform engineering and its adoption across industries. Additionally, it also makes recommendations for further research for understanding, advancing the state of the art, and fostering the adoption of platform engineering within the software development industry.</p>\u0000 </div>","PeriodicalId":48898,"journal":{"name":"Journal of Software-Evolution and Process","volume":"38 4","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147683632","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}