A Systematic Review of API Evolution Literature

2022 ◽  
Vol 54 (8) ◽  
pp. 1-36
Author(s):  
Maxime Lamothe ◽  
Yann-Gaël Guéhéneuc ◽  
Weiyi Shang
Keyword(s):  
Programming Languages ◽  
Research Evaluation ◽  
State Of The Art ◽  
Publication Trends ◽  
Current State ◽  
Software Artifact ◽  
Application Programming ◽  
New Challenges ◽  
The Impact ◽  
Programming Interfaces

Recent software advances have led to an expansion of the development and usage of application programming interfaces (APIs). From millions of Android packages (APKs) available on Google Store to millions of open-source packages available in Maven, PyPI, and npm, APIs have become an integral part of software development. Like any software artifact, software APIs evolve and suffer from this evolution. Prior research has uncovered many challenges to the development, usage, and evolution of APIs. While some challenges have been studied and solved, many remain. These challenges are scattered in the literature, which hides advances and cloaks the remaining challenges. In this systematic literature review on APIs and API evolution, we uncover and describe publication trends and trending topics. We compile common research goals, evaluation methods, metrics, and subjects. We summarize the current state-of-the-art and outline known existing challenges as well as new challenges uncovered during this review. We conclude that the main remaining challenges related to APIs and API evolution are (1) automatically identifying and leveraging factors that drive API changes, (2) creating and using uniform benchmarks for research evaluation, and (3) understanding the impact of API evolution on API developers and users with respect to various programming languages.

scholarly journals Generating Adversarial Examples for Holding Robustness of Source Code Processing Models

2020 ◽  
Vol 34 (01) ◽  
pp. 1169-1176
Author(s):  
Huangzhao Zhang ◽  
Zhuo Li ◽  
Ge Li ◽  
Lei Ma ◽  
Yang Liu ◽  
...  
Keyword(s):  
Programming Languages ◽  
State Of The Art ◽  
Source Code ◽  
Natural Languages ◽  
Current State ◽  
Automated Processing ◽  
Adversarial Examples ◽  
Adversarial Training ◽  
New Challenges ◽  
And Performance

Automated processing, analysis, and generation of source code are among the key activities in software and system lifecycle. To this end, while deep learning (DL) exhibits a certain level of capability in handling these tasks, the current state-of-the-art DL models still suffer from non-robust issues and can be easily fooled by adversarial attacks.Different from adversarial attacks for image, audio, and natural languages, the structured nature of programming languages brings new challenges. In this paper, we propose a Metropolis-Hastings sampling-based identifier renaming technique, named \fullmethod (\method), which generates adversarial examples for DL models specialized for source code processing. Our in-depth evaluation on a functionality classification benchmark demonstrates the effectiveness of \method in generating adversarial examples of source code. The higher robustness and performance enhanced through our adversarial training with \method further confirms the usefulness of DL models-based method for future fully automated source code processing.

scholarly journals Smoothing additive manufactured parts using ns-pulsed laser radiation

2021 ◽  
Author(s):  
Florian Kuisat ◽  
Fernando Lasagni ◽  
Andrés Fabián Lasagni
Keyword(s):  
Surface Roughness ◽  
Mechanical Performance ◽  
State Of The Art ◽  
Pulsed Laser ◽  
Industrial Applications ◽  
Laser Source ◽  
Pulsed Laser Radiation ◽  
Current State ◽  
The Impact

AbstractIt is well known that the surface topography of a part can affect its mechanical performance, which is typical in additive manufacturing. In this context, we report about the surface modification of additive manufactured components made of Titanium 64 (Ti64) and Scalmalloy®, using a pulsed laser, with the aim of reducing their surface roughness. In our experiments, a nanosecond-pulsed infrared laser source with variable pulse durations between 8 and 200 ns was applied. The impact of varying a large number of parameters on the surface quality of the smoothed areas was investigated. The results demonstrated a reduction of surface roughness Sa by more than 80% for Titanium 64 and by 65% for Scalmalloy® samples. This allows to extend the applicability of additive manufactured components beyond the current state of the art and break new ground for the application in various industrial applications such as in aerospace.

Evaluating the Current State of Application Programming Interfaces for Verifiable Credentials

2021 ◽  
Author(s):  
Nikesh Lalchandani ◽  
Frank Jiang ◽  
Jongkil Jay Jeong ◽  
Yevhen Zolotavkin ◽  
Robin Doss
Keyword(s):  
Application Programming Interfaces ◽  
Current State ◽  
Application Programming ◽  
Programming Interfaces

scholarly journals Climate-dependent propagation of precipitation uncertainty into the water cycle

2020 ◽  
Author(s):  
Ali Fallah ◽  
Sungmin O ◽  
Rene Orth
Keyword(s):  
Hydrological Model ◽  
Water Cycle ◽  
State Of The Art ◽  
Rain Gauge ◽  
Multiple Sources ◽  
Current State ◽  
Wide Range ◽  
The Impact ◽  
Conceptual Hydrological Model

Abstract. Precipitation is a crucial variable for hydro-meteorological applications. Unfortunately, rain gauge measurements are sparse and unevenly distributed, which substantially hampers the use of in-situ precipitation data in many regions of the world. The increasing availability of high-resolution gridded precipitation products presents a valuable alternative, especially over gauge-sparse regions. Nevertheless, uncertainties and corresponding differences across products can limit the applicability of these data. This study examines the usefulness of current state-of-the-art precipitation datasets in hydrological modelling. For this purpose, we force a conceptual hydrological model with multiple precipitation datasets in > 200 European catchments. We consider a wide range of precipitation products, which are generated via (1) interpolation of gauge measurements (E-OBS and GPCC V.2018), (2) combination of multiple sources (MSWEP V2) and (3) data assimilation into reanalysis models (ERA-Interim, ERA5, and CFSR). For each catchment, runoff and evapotranspiration simulations are obtained by forcing the model with the various precipitation products. Evaluation is done at the monthly time scale during the period of 1984–2007. We find that simulated runoff values are highly dependent on the accuracy of precipitation inputs, and thus show significant differences between the simulations. By contrast, simulated evapotranspiration is generally much less influenced. The results are further analysed with respect to different hydro-climatic regimes. We find that the impact of precipitation uncertainty on simulated runoff increases towards wetter regions, while the opposite is observed in the case of evapotranspiration. Finally, we perform an indirect performance evaluation of the precipitation datasets by comparing the runoff simulations with streamflow observations. Thereby, E-OBS yields the best agreement, while furthermore ERA5, GPCC V.2018 and MSWEP V2 show good performance. In summary, our findings highlight a climate-dependent propagation of precipitation uncertainty through the water cycle; while runoff is strongly impacted in comparatively wet regions such as Central Europe, there are increasing implications on evapotranspiration towards drier regions.

Modelling Nitrogen Deposition on a Local Scale—A Review of the Current State of the Art

2006 ◽  
Vol 3 (5) ◽  
pp. 317 ◽  
Author(s):  
Ole Hertel ◽  
Carsten Ambelas Skjøth ◽  
Per Løfstrøm ◽  
Camilla Geels ◽  
Lise Marie Frohn ◽  
...  
Keyword(s):  
Nitrogen Deposition ◽  
Environmental Assessment ◽  
State Of The Art ◽  
N Deposition ◽  
Model Systems ◽  
Special Focus ◽  
Ammonia Emissions ◽  
High Nitrogen ◽  
Current State ◽  
The Impact

Abstract. Local ammonia emissions from agricultural activities are often associated with high nitrogen deposition in the close vicinity of the sources. High nitrogen (N) inputs may significantly affect the local ecosystems. Over a longer term, high loads may change the composition of the ecosystems, leading to a general decrease in local biodiversity. In Europe there is currently a significant focus on the impact of atmospheric N load on local ecosystems among environmental managers and policy makers. Model tools designed for application in N deposition assessment and aimed for use in the regulation of anthropogenic nitrogen emissions are, therefore, under development in many European countries. The aim of this paper is to present a review of the current understanding and modelling parameterizations of atmospheric N deposition. A special focus is on the development of operational tools for use in environmental assessment and regulation related to agricultural ammonia emissions. For the often large number of environmental impact assessments needed to be carried out by local environmental managers there is, furthermore, a need for simple and fast model systems. These systems must capture the most important aspects of dispersion and deposition of N in the nearby environment of farms with animal production. The paper includes a discussion on the demands on the models applied in environmental assessment and regulation and how these demands are fulfilled in current state-of-the-art models.

scholarly journals DeepAM: Migrate APIs with Multi-modal Sequence to Sequence Learning

2017 ◽  
Author(s):  
Xiaodong Gu ◽  
Hongyu Zhang ◽  
Dongmei Zhang ◽  
Sunghun Kim
Keyword(s):  
Sequence Learning ◽  
Large Scale ◽  
Intelligent System ◽  
State Of The Art ◽  
Source Code ◽  
Computer Programs ◽  
Experimental Results ◽  
Multiple Devices ◽  
Application Programming ◽  
Programming Interfaces

Computer programs written in one language are often required to be ported to other languages to support multiple devices and environments. When programs use language specific APIs (Application Programming Interfaces), it is very challenging to migrate these APIs to the corresponding APIs written in other languages. Existing approaches mine API mappings from projects that have corresponding versions in two languages. They rely on the sparse availability of bilingual projects, thus producing a limited number of API mappings. In this paper, we propose an intelligent system called DeepAM for automatically mining API mappings from a large-scale code corpus without bilingual projects. The key component of DeepAM is based on the multi-modal sequence to sequence learning architecture that aims to learn joint semantic representations of bilingual API sequences from big source code data. Experimental results indicate that DeepAM significantly increases the accuracy of API mappings as well as the number of API mappings when compared with the state-of-the-art approaches.

Programming Interfaces for Realtime and Cloud-Based Computing

2012 ◽  
pp. 959-975
Author(s):  
Gregory Katsaros ◽  
Tommaso Cucinotta
Keyword(s):  
Quality Of Service ◽  
Real Time ◽  
State Of The Art ◽  
New Products ◽  
The State ◽  
New Challenges ◽  
Real Time Computing ◽  
Programming Interfaces ◽  
Real Time Application

The appearance of different business roles according to this classification, potentially with differing interests, introduces new challenges with regard to the tools and mechanisms put in place in order to enable the efficient provisioning of services. Security, Quality of Service (QoS) assurance, and real-time capabilities are just a few issues that the providers are trying to tackle and integrate within the new products and services that they offer. In this chapter, we make an overview of the approaches that aim to APIs for real-time computing. In the first part of this chapter, several Real-Time Application Interfaces will be presented and compared. After that, we will document the state-of-the-art regarding the Cloud APIs available and analyze the architecture and the technologies that they support.

Online Social Exergames for Seniors

2020 ◽  
pp. 1599-1631
Author(s):  
Stathis Th. Konstantinidis ◽  
Ellen Brox ◽  
Per Egil Kummervold ◽  
Josef Hallberg ◽  
Gunn Evertsen ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Physical Activity ◽  
Physical Training ◽  
State Of The Art ◽  
Social Contact ◽  
High Quality ◽  
Current State ◽  
The Future ◽  
The Impact

The population is getting older, and the resources for care will be even more limited in the future than they are now. There is thus an aim for the society that the seniors can manage themselves as long as possible, while at the same time keeping a high quality of life. Physical activity is important to stay fit, and social contact is important for the quality of life. The aim of this chapter is to provide a state-of-the-art of online social exergames for seniors, providing glimpses of senior users' opinions and games limitations. The importance of the motivational techniques is emphasized, as well as the impact that the exergames have to seniors. It contributes to the book objectives focusing on current state and practice in health games for physical training and rehabilitation and the use of gamification, exploring future opportunities and uses of gamification in eHealth and discussing the respective challenges and limitations.

scholarly journals Enterosorption in the Treatment of Heavy Metal Poisoning

2021 ◽  
Author(s):  
Sergey Mikhalovsky ◽  
Oleksandr Voytko ◽  
Violetta Demchenko ◽  
Pavlo Demchenko
Keyword(s):  
Heavy Metals ◽  
Heavy Metal ◽  
Chronic Exposure ◽  
State Of The Art ◽  
Cost Effective ◽  
Heavy Metal Poisoning ◽  
Industrial Activities ◽  
Current State ◽  
Metal Poisoning ◽  
The Impact

Enterosorption is a cost-effective and efficient approach to reducing the impact of chronic exposure to heavy metals and radionuclides. As an auxiliary method to medical treatment, it can protect population chronically exposed to the intake of heavy metals or radioactivity due to industrial activities or in the aftermath of technogenic or natural accidents. This paper assesses the current state of the art in the treatment of acute and chronic heavy metal poisoning.

scholarly journals State-of-the-art surgery for pancreatic cancer

2021 ◽  
Author(s):  
Anna Nießen ◽  
Thilo Hackert
Keyword(s):  
Pancreatic Cancer ◽  
Pancreatic Surgery ◽  
Best Practice ◽  
New Technologies ◽  
State Of The Art ◽  
Surgical Techniques ◽  
Complication Management ◽  
Oncological Treatment ◽  
Current State ◽  
The Impact

Abstract Background The d evelopment of surgical techniques and specialization and specifically complication management in pancreatic surgery have improved surgical outcomes as well as oncological results in pancreatic surgery in recent decades. Historical morbidity and especially mortality rates of up to 80% have decreased to below 5% today. This review summarizes the current state of the art in pancreatic cancer surgery. Methods The present literature and clinical experience are summarized to give an overview of the present best practice in pancreatic surgery as one of the most advanced surgical disciplines today. Results Based on the available literature, three important aspects contribute to best patient care in pancreatic surgery, namely, surgical progress, interdisciplinary complication management, and multimodal oncological treatment in case of pancreatic cancer. In addition, minimally invasive and robotic procedures are currently fields of development and specific topics of research. Conclusion In experienced hands, pancreatic surgery—despite being one of the most challenging fields of surgery—is a safe domain today. The impact of multimodal, especially adjuvant, therapy for oncological indications is well established and evidence-based. New technologies are evolving and will be evaluated with high-evidence studies in the near future.

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