Reliability is one of the most important quality attributes of a software system, addressing the system’s ability to perform the required functionalities under stated conditions, for a stated period of time. Nowadays, a system failure could threaten the safety of human life. Thus, assessing reliability became one of the software engineering‘s holy grails. Our approach wants to establish based on what project’s characteristics we obtain the best bug-oriented reliability prediction model. The pillars on which we base our approach are the metric introduced to estimate one aspect of reliability using bugs, and the Chidamber and Kemerer (CK) metrics to assess reliability in the early stages of development. The methodology used for prediction is a feed-forward neural network with back-propagation learning. Five different projects are used to validate the proposed approach for reliability prediction. The results indicate that CK metrics are promising in predicting reliability using a neural network model. The experiments also analyze if the type of project used in the development of the prediction model influences the quality of the prediction. As a result of the operated experiments using both within-project and cross-project validation, the best prediction model was obtained using PDE (PlugIn characteristic) for MY project (Task characteristic).
{"title":"Towards a Reliability Prediction Model based on Internal Structure and Post-Release Defects Using Neural Networks","authors":"A. Vescan, C. Serban, Alisa-Daniela Budur","doi":"10.1145/3463274.3463363","DOIUrl":"https://doi.org/10.1145/3463274.3463363","url":null,"abstract":"Reliability is one of the most important quality attributes of a software system, addressing the system’s ability to perform the required functionalities under stated conditions, for a stated period of time. Nowadays, a system failure could threaten the safety of human life. Thus, assessing reliability became one of the software engineering‘s holy grails. Our approach wants to establish based on what project’s characteristics we obtain the best bug-oriented reliability prediction model. The pillars on which we base our approach are the metric introduced to estimate one aspect of reliability using bugs, and the Chidamber and Kemerer (CK) metrics to assess reliability in the early stages of development. The methodology used for prediction is a feed-forward neural network with back-propagation learning. Five different projects are used to validate the proposed approach for reliability prediction. The results indicate that CK metrics are promising in predicting reliability using a neural network model. The experiments also analyze if the type of project used in the development of the prediction model influences the quality of the prediction. As a result of the operated experiments using both within-project and cross-project validation, the best prediction model was obtained using PDE (PlugIn characteristic) for MY project (Task characteristic).","PeriodicalId":328024,"journal":{"name":"Proceedings of the 25th International Conference on Evaluation and Assessment in Software Engineering","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125722893","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Software development processes play a key role in the software and system development life cycle. Processes are becoming complex and evolve rapidly due to the modern-day continuous software engineering (CSE) concepts, which are mainly based on continuous integration, continuous delivery, infrastructure-as-code, automation and more. The fast growing Chinese software development industry adopts various processes to achieve potential benefits offered in the international market. This study is conducted with the aim to investigate the trends of processes in practice in the Chinese industry. The survey questionnaire data is collected from 34 practitioners working in software development firms across the China and the results highlight that iterative and agile processes are extensively used in industrial setting. Furthermore, agile and traditional approaches are combined to develop the hybrid processes. Most of the participants are satisfied using the current development processes, however, they show interest to continuously improve the existing process models and methods. Finally, we noticed that majority of the software development organizations used the ISO 9001 standard for process assessment and improvement activities. The given results provide preliminary overview of processes deployed in the Chinese industry.
{"title":"System and Software Processes in Practice: Insights from Chinese Industry","authors":"Peng Zhou, A. Khan, Peng Liang, Sher Badshah","doi":"10.1145/3463274.3463786","DOIUrl":"https://doi.org/10.1145/3463274.3463786","url":null,"abstract":"Software development processes play a key role in the software and system development life cycle. Processes are becoming complex and evolve rapidly due to the modern-day continuous software engineering (CSE) concepts, which are mainly based on continuous integration, continuous delivery, infrastructure-as-code, automation and more. The fast growing Chinese software development industry adopts various processes to achieve potential benefits offered in the international market. This study is conducted with the aim to investigate the trends of processes in practice in the Chinese industry. The survey questionnaire data is collected from 34 practitioners working in software development firms across the China and the results highlight that iterative and agile processes are extensively used in industrial setting. Furthermore, agile and traditional approaches are combined to develop the hybrid processes. Most of the participants are satisfied using the current development processes, however, they show interest to continuously improve the existing process models and methods. Finally, we noticed that majority of the software development organizations used the ISO 9001 standard for process assessment and improvement activities. The given results provide preliminary overview of processes deployed in the Chinese industry.","PeriodicalId":328024,"journal":{"name":"Proceedings of the 25th International Conference on Evaluation and Assessment in Software Engineering","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130107779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Context: Sustainability has become an important topic for researchers and is gaining popularity among software development companies, but integrating it into their development processes is still lacking. Objectives: This paper aimed to discuss the purpose of doctoral research, the research questions, the steps to answer the research questions, and the research's current progress concerning sustainability in the software development life cycle. Results: I have presented the high-level plans for the doctoral research and outlined the first part of the results of phase 1. As part of this phase 1, I have conducted an extensive literature review to collect data about sustainability in companies' agile methods. I found only a few studies reporting sustainability in agile software development, and this finding proposes that either this field was not studied, or the results have not been widely published, indicating a gap in research.
{"title":"Supporting sustainability design through agile software development","authors":"Hatef Shamshiri","doi":"10.1145/3463274.3463347","DOIUrl":"https://doi.org/10.1145/3463274.3463347","url":null,"abstract":"Context: Sustainability has become an important topic for researchers and is gaining popularity among software development companies, but integrating it into their development processes is still lacking. Objectives: This paper aimed to discuss the purpose of doctoral research, the research questions, the steps to answer the research questions, and the research's current progress concerning sustainability in the software development life cycle. Results: I have presented the high-level plans for the doctoral research and outlined the first part of the results of phase 1. As part of this phase 1, I have conducted an extensive literature review to collect data about sustainability in companies' agile methods. I found only a few studies reporting sustainability in agile software development, and this finding proposes that either this field was not studied, or the results have not been widely published, indicating a gap in research.","PeriodicalId":328024,"journal":{"name":"Proceedings of the 25th International Conference on Evaluation and Assessment in Software Engineering","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131364429","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Code completion tools are increasingly important when developing modern software. Recently, statistical language modeling techniques have achieved great success in the code completion task. However, two major issues with these techniques severely affect the performance of neural language models (NLMs) of code completion. a) Long-range dependences are common in program source code. b) New and rare vocabulary in code is much higher than natural language. To address the challenges above, in this paper, we propose code completion with a memory mechanism and a copy mechanism (CCMC). To capture the long-range dependencies in the program source code, we employ Transformer-XL as our base model. To utilize the locally repeated terms in program source code, we apply the pointer network into our base model and design CopyMask to improve the training efficiency, which is inspired by masked multihead attention in the transformer decoder. To combine the long-range dependency modeling ability from Transformer-XL and the ability to copy the input token to output from the pointer network, we design a memory mechanism and a copy mechanism. Through our memory mechanism, our model can uniformly manage the context used by Transformer-XL and pointer network. Through our copy mechanism, our model can either generate a within-vocabulary token or copy an out-of-vocabulary (OOV) token from inputs. Experiments on a real-world dataset demonstrate the effectiveness of our CCMC on the code completion task.
{"title":"CCMC: Code Completion with a Memory Mechanism and a Copy Mechanism","authors":"Hao Yang, Li Kuang","doi":"10.1145/3463274.3463332","DOIUrl":"https://doi.org/10.1145/3463274.3463332","url":null,"abstract":"Code completion tools are increasingly important when developing modern software. Recently, statistical language modeling techniques have achieved great success in the code completion task. However, two major issues with these techniques severely affect the performance of neural language models (NLMs) of code completion. a) Long-range dependences are common in program source code. b) New and rare vocabulary in code is much higher than natural language. To address the challenges above, in this paper, we propose code completion with a memory mechanism and a copy mechanism (CCMC). To capture the long-range dependencies in the program source code, we employ Transformer-XL as our base model. To utilize the locally repeated terms in program source code, we apply the pointer network into our base model and design CopyMask to improve the training efficiency, which is inspired by masked multihead attention in the transformer decoder. To combine the long-range dependency modeling ability from Transformer-XL and the ability to copy the input token to output from the pointer network, we design a memory mechanism and a copy mechanism. Through our memory mechanism, our model can uniformly manage the context used by Transformer-XL and pointer network. Through our copy mechanism, our model can either generate a within-vocabulary token or copy an out-of-vocabulary (OOV) token from inputs. Experiments on a real-world dataset demonstrate the effectiveness of our CCMC on the code completion task.","PeriodicalId":328024,"journal":{"name":"Proceedings of the 25th International Conference on Evaluation and Assessment in Software Engineering","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124828335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Correlative studies carried out by different experts have cited a number of impediments to the growth of cloud computing technology; at the top of the list is security and data privacy issues. More so, a systematic mapping study which was conducted at the start of this research, revealed that the most prevalent cloud security issues are a consequence of poor architecture. 73 percent of literature surveyed also revealed that frameworks and reference architectures are one of the most effective ways of preventing security and data privacy breaches within a cloud computing environment as these issues are addressed during the requirements phase, prior to deployment. [1], [14] This research seeks to explore a preventative approach to cloud security breaches through the use of reference architectures. Firstly, we investigate the main causes of cloud security breaches and then, we analyse existing reference architectures with the aim of designing a universal security framework usable across multi-cloud computing platforms.
{"title":"A Reference Architecture for Validating Security Across Multi-Cloud Computing Systems","authors":"Henry Edet","doi":"10.1145/3463274.3463345","DOIUrl":"https://doi.org/10.1145/3463274.3463345","url":null,"abstract":"Correlative studies carried out by different experts have cited a number of impediments to the growth of cloud computing technology; at the top of the list is security and data privacy issues. More so, a systematic mapping study which was conducted at the start of this research, revealed that the most prevalent cloud security issues are a consequence of poor architecture. 73 percent of literature surveyed also revealed that frameworks and reference architectures are one of the most effective ways of preventing security and data privacy breaches within a cloud computing environment as these issues are addressed during the requirements phase, prior to deployment. [1], [14] This research seeks to explore a preventative approach to cloud security breaches through the use of reference architectures. Firstly, we investigate the main causes of cloud security breaches and then, we analyse existing reference architectures with the aim of designing a universal security framework usable across multi-cloud computing platforms.","PeriodicalId":328024,"journal":{"name":"Proceedings of the 25th International Conference on Evaluation and Assessment in Software Engineering","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125493099","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
L. Martins, V. Brito, Daniel Feitosa, Larissa Rocha, H. Costa, I. Machado
The teaching-learning process may require specific pedagogical approaches to establish a relationship with industry practices. Recently, some studies investigated the educators’ perspectives and the undergraduate courses curriculum to identify potential weaknesses and solutions for the software testing teaching process. However, it is still unclear how the practitioners evaluate the acquisition of knowledge about software testing in undergraduate courses. This study carried out an expert survey with 68 newly graduated practitioners to determine what the industry expects from them and what they learned in academia. The yielded results indicated that those practitioners learned at a similar rate as others with a long industry experience. Also, they studied less than half of the 35 software testing topics collected in the survey and took industry-backed extracurricular courses to complement their learning. Additionally, our findings point out a set of implications for future research, as the respondents’ learning difficulties (e.g., lack of learning sources) and the gap between academic education and industry expectations (e.g., certifications).
{"title":"From Blackboard to the Office: A Look Into How Practitioners Perceive Software Testing Education","authors":"L. Martins, V. Brito, Daniel Feitosa, Larissa Rocha, H. Costa, I. Machado","doi":"10.1145/3463274.3463338","DOIUrl":"https://doi.org/10.1145/3463274.3463338","url":null,"abstract":"The teaching-learning process may require specific pedagogical approaches to establish a relationship with industry practices. Recently, some studies investigated the educators’ perspectives and the undergraduate courses curriculum to identify potential weaknesses and solutions for the software testing teaching process. However, it is still unclear how the practitioners evaluate the acquisition of knowledge about software testing in undergraduate courses. This study carried out an expert survey with 68 newly graduated practitioners to determine what the industry expects from them and what they learned in academia. The yielded results indicated that those practitioners learned at a similar rate as others with a long industry experience. Also, they studied less than half of the 35 software testing topics collected in the survey and took industry-backed extracurricular courses to complement their learning. Additionally, our findings point out a set of implications for future research, as the respondents’ learning difficulties (e.g., lack of learning sources) and the gap between academic education and industry expectations (e.g., certifications).","PeriodicalId":328024,"journal":{"name":"Proceedings of the 25th International Conference on Evaluation and Assessment in Software Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130119744","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jithin Cheriyan, Bastin Tony Roy Savarimuthu, Stephen Cranefield
Software Engineering (SE) communities such as Stack Overflow have become unwelcoming, particularly through members’ use of offensive language. Research has shown that offensive language drives users away from active engagement within these platforms. This work aims to explore this issue more broadly by investigating the nature of offensive language in comments posted by users in four prominent SE platforms – GitHub, Gitter, Slack and Stack Overflow (SO). It proposes an approach to detect and classify offensive language in SE communities by adopting natural language processing and deep learning techniques. Further, a Conflict Reduction System (CRS), which identifies offence and then suggests what changes could be made to minimize offence has been proposed. Beyond showing the prevalence of offensive language in over 1 million comments from four different communities which ranges from 0.07% to 0.43%, our results show promise in successful detection and classification of such language. The CRS system has the potential to drastically reduce manual moderation efforts to detect and reduce offence in SE communities.
{"title":"Towards offensive language detection and reduction in four Software Engineering communities","authors":"Jithin Cheriyan, Bastin Tony Roy Savarimuthu, Stephen Cranefield","doi":"10.1145/3463274.3463805","DOIUrl":"https://doi.org/10.1145/3463274.3463805","url":null,"abstract":"Software Engineering (SE) communities such as Stack Overflow have become unwelcoming, particularly through members’ use of offensive language. Research has shown that offensive language drives users away from active engagement within these platforms. This work aims to explore this issue more broadly by investigating the nature of offensive language in comments posted by users in four prominent SE platforms – GitHub, Gitter, Slack and Stack Overflow (SO). It proposes an approach to detect and classify offensive language in SE communities by adopting natural language processing and deep learning techniques. Further, a Conflict Reduction System (CRS), which identifies offence and then suggests what changes could be made to minimize offence has been proposed. Beyond showing the prevalence of offensive language in over 1 million comments from four different communities which ranges from 0.07% to 0.43%, our results show promise in successful detection and classification of such language. The CRS system has the potential to drastically reduce manual moderation efforts to detect and reduce offence in SE communities.","PeriodicalId":328024,"journal":{"name":"Proceedings of the 25th International Conference on Evaluation and Assessment in Software Engineering","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134159583","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
P. Sharma, Bastin Tony Roy Savarimuthu, N. Stanger
Governance has been highlighted as a key factor in the success of an Open Source Software (OSS) project. It is generally seen that in a mixed meritocracy and autocracy governance model, the decision-making (DM) responsibility regarding what features are included in the OSS is shared among members from select roles; prominently the project leader. However, less examination has been made whether members from these roles are also prominent in DM discussions and how decisions are made, to show they play an integral role in the success of the project. We believe that to establish their influence, it is necessary to examine not only discussions of proposals in which the project leader makes the decisions, but also those where others make the decisions. Therefore, in this study, we examine the prominence of members performing different roles in: (i) making decisions, (ii) performing certain social roles in DM discussions (e.g., discussion starters), (iii) contributing to the OSS development social network through DM discussions, and (iv) how decisions are made under both scenarios. We examine these aspects in the evolution of the well-known Python project. We carried out a data-driven longitudinal study of their email communication spanning 20 years, comprising about 1.5 million emails. These emails contain decisions for 466 Python Enhancement Proposals (PEPs) that document the language’s evolution. Our findings make the influence of different roles transparent to future (new) members, other stakeholders, and more broadly, to the OSS research community.
{"title":"Influence of Roles in Decision-Making during OSS Development — A Study of Python","authors":"P. Sharma, Bastin Tony Roy Savarimuthu, N. Stanger","doi":"10.1145/3463274.3463326","DOIUrl":"https://doi.org/10.1145/3463274.3463326","url":null,"abstract":"Governance has been highlighted as a key factor in the success of an Open Source Software (OSS) project. It is generally seen that in a mixed meritocracy and autocracy governance model, the decision-making (DM) responsibility regarding what features are included in the OSS is shared among members from select roles; prominently the project leader. However, less examination has been made whether members from these roles are also prominent in DM discussions and how decisions are made, to show they play an integral role in the success of the project. We believe that to establish their influence, it is necessary to examine not only discussions of proposals in which the project leader makes the decisions, but also those where others make the decisions. Therefore, in this study, we examine the prominence of members performing different roles in: (i) making decisions, (ii) performing certain social roles in DM discussions (e.g., discussion starters), (iii) contributing to the OSS development social network through DM discussions, and (iv) how decisions are made under both scenarios. We examine these aspects in the evolution of the well-known Python project. We carried out a data-driven longitudinal study of their email communication spanning 20 years, comprising about 1.5 million emails. These emails contain decisions for 466 Python Enhancement Proposals (PEPs) that document the language’s evolution. Our findings make the influence of different roles transparent to future (new) members, other stakeholders, and more broadly, to the OSS research community.","PeriodicalId":328024,"journal":{"name":"Proceedings of the 25th International Conference on Evaluation and Assessment in Software Engineering","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132768396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jiahui Geng, Neel Kanwal, M. Jaatun, Chunming Rong
We have entered the era of big data, and it is considered to be the ”fuel” for the flourishing of artificial intelligence applications. The enactment of the EU General Data Protection Regulation (GDPR) raises concerns about individuals’ privacy in big data. Federated learning (FL) emerges as a functional solution that can help build high-performance models shared among multiple parties while still complying with user privacy and data confidentiality requirements. Although FL has been intensively studied and used in real applications, there is still limited research related to its prospects and applications as a FLaaS (Federated Learning as a Service) to interested 3rd parties. In this paper, we present a FLaaS system: DID-eFed, where FL is facilitated by decentralized identities (DID) and a smart contract. DID enables a more flexible and credible decentralized access management in our system, while the smart contract offers a frictionless and less error-prone process. We describe particularly the scenario where our DID-eFed enables the FLaaS among hospitals and research institutions.
{"title":"DID-eFed: Facilitating Federated Learning as a Service with Decentralized Identities","authors":"Jiahui Geng, Neel Kanwal, M. Jaatun, Chunming Rong","doi":"10.1145/3463274.3463352","DOIUrl":"https://doi.org/10.1145/3463274.3463352","url":null,"abstract":"We have entered the era of big data, and it is considered to be the ”fuel” for the flourishing of artificial intelligence applications. The enactment of the EU General Data Protection Regulation (GDPR) raises concerns about individuals’ privacy in big data. Federated learning (FL) emerges as a functional solution that can help build high-performance models shared among multiple parties while still complying with user privacy and data confidentiality requirements. Although FL has been intensively studied and used in real applications, there is still limited research related to its prospects and applications as a FLaaS (Federated Learning as a Service) to interested 3rd parties. In this paper, we present a FLaaS system: DID-eFed, where FL is facilitated by decentralized identities (DID) and a smart contract. DID enables a more flexible and credible decentralized access management in our system, while the smart contract offers a frictionless and less error-prone process. We describe particularly the scenario where our DID-eFed enables the FLaaS among hospitals and research institutions.","PeriodicalId":328024,"journal":{"name":"Proceedings of the 25th International Conference on Evaluation and Assessment in Software Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129470940","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Finding bugs in a commercial cyber-physical system (CPS) development tool such as Simulink is hard as its codebase contains millions of lines of code and complete formal language specifications are not available. While deep learning techniques promise to learn such language specifications from sample models, deep learning needs a large number of training data to work well. SLGPT addresses this problem by using transfer learning to leverage the powerful Generative Pre-trained Transformer 2 (GPT-2) model, which has been pre-trained on a large set of training data. SLGPT adapts GPT-2 to Simulink with both randomly generated models and models mined from open-source repositories. SLGPT produced Simulink models that are both more similar to open-source models than its closest competitor, DeepFuzzSL, and found a super-set of the Simulink development toolchain bugs found by DeepFuzzSL.
{"title":"SLGPT: Using Transfer Learning to Directly Generate Simulink Model Files and Find Bugs in the Simulink Toolchain","authors":"S. L. Shrestha, Christoph Csallner","doi":"10.1145/3463274.3463806","DOIUrl":"https://doi.org/10.1145/3463274.3463806","url":null,"abstract":"Finding bugs in a commercial cyber-physical system (CPS) development tool such as Simulink is hard as its codebase contains millions of lines of code and complete formal language specifications are not available. While deep learning techniques promise to learn such language specifications from sample models, deep learning needs a large number of training data to work well. SLGPT addresses this problem by using transfer learning to leverage the powerful Generative Pre-trained Transformer 2 (GPT-2) model, which has been pre-trained on a large set of training data. SLGPT adapts GPT-2 to Simulink with both randomly generated models and models mined from open-source repositories. SLGPT produced Simulink models that are both more similar to open-source models than its closest competitor, DeepFuzzSL, and found a super-set of the Simulink development toolchain bugs found by DeepFuzzSL.","PeriodicalId":328024,"journal":{"name":"Proceedings of the 25th International Conference on Evaluation and Assessment in Software Engineering","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116473054","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：