Pub Date : 2013-11-01DOI: 10.1109/ISSREW.2013.6688850
Noriyoshi Kuno, Tsuyoshi Nakajima, M. Matsushita, Katsuro Inoue
The effectiveness of peer review meetings in software development has been discussed for many years. Porter concludes that peer review meetings do not contribute significantly to defect extraction. This paper shows contradictory data to the Porter's findings and our interpretation for them.
{"title":"A study on the effectiveness of peer review meeting","authors":"Noriyoshi Kuno, Tsuyoshi Nakajima, M. Matsushita, Katsuro Inoue","doi":"10.1109/ISSREW.2013.6688850","DOIUrl":"https://doi.org/10.1109/ISSREW.2013.6688850","url":null,"abstract":"The effectiveness of peer review meetings in software development has been discussed for many years. Porter concludes that peer review meetings do not contribute significantly to defect extraction. This paper shows contradictory data to the Porter's findings and our interpretation for them.","PeriodicalId":332420,"journal":{"name":"2013 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131324596","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}
Pub Date : 2013-11-01DOI: 10.1109/ISSREW.2013.6688904
Domenico Cotroneo, Flavio Frattini, R. Natella, R. Pietrantuono
We analyze performance degradation phenomena due to software aging on a real supercomputer deployed at the Federico II University of Naples, by considering a dataset of ten months of operational usage. We adopted a statistical approach for identifying when and where the supercomputer experienced a performance degradation trend. The analysis pinpointed performance degradation trends that were actually caused by the gradual error accumulation within basic software of the supercomputer.
{"title":"Performance degradation analysis of a supercomputer","authors":"Domenico Cotroneo, Flavio Frattini, R. Natella, R. Pietrantuono","doi":"10.1109/ISSREW.2013.6688904","DOIUrl":"https://doi.org/10.1109/ISSREW.2013.6688904","url":null,"abstract":"We analyze performance degradation phenomena due to software aging on a real supercomputer deployed at the Federico II University of Naples, by considering a dataset of ten months of operational usage. We adopted a statistical approach for identifying when and where the supercomputer experienced a performance degradation trend. The analysis pinpointed performance degradation trends that were actually caused by the gradual error accumulation within basic software of the supercomputer.","PeriodicalId":332420,"journal":{"name":"2013 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122487318","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}
Pub Date : 2013-11-01DOI: 10.1109/ISSREW.2013.6688886
Ron Morillo, J. Lai, L. Meshkat
Summary form only given. This paper provides a summary of a task that was undertaken at the Jet Propulsion Laboratory to review the anomalies captured in the “Problem Failure Reporting” database for the Curiosity Flight Software and identify the critical areas for improvement in the software design and development processes across the flight projects. The team reviewed a significant portion of the thousands of PFR's that were recorded in this database and identified their corresponding defect signatures: where the defect had been inserted and the cracks it had fallen through during the remainder of the development and testing phases. Of particular interest were the defects that had the longest distance from injection to detection and those which had the highest severity. Further analyses such as identification of modules with the highest defect density and detection and testing mechanisms with inadequate detection rates were also conducted. The results obtained to date are compelling and their implications may include significant changes and upgrades to the current requirements engineering and testing methodologies employed at JPL.
{"title":"Forensic study of the Curiosity Flight Software anomalies","authors":"Ron Morillo, J. Lai, L. Meshkat","doi":"10.1109/ISSREW.2013.6688886","DOIUrl":"https://doi.org/10.1109/ISSREW.2013.6688886","url":null,"abstract":"Summary form only given. This paper provides a summary of a task that was undertaken at the Jet Propulsion Laboratory to review the anomalies captured in the “Problem Failure Reporting” database for the Curiosity Flight Software and identify the critical areas for improvement in the software design and development processes across the flight projects. The team reviewed a significant portion of the thousands of PFR's that were recorded in this database and identified their corresponding defect signatures: where the defect had been inserted and the cracks it had fallen through during the remainder of the development and testing phases. Of particular interest were the defects that had the longest distance from injection to detection and those which had the highest severity. Further analyses such as identification of modules with the highest defect density and detection and testing mechanisms with inadequate detection rates were also conducted. The results obtained to date are compelling and their implications may include significant changes and upgrades to the current requirements engineering and testing methodologies employed at JPL.","PeriodicalId":332420,"journal":{"name":"2013 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW)","volume":"194 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121242008","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}
Pub Date : 2013-11-01DOI: 10.1109/ISSREW.2013.6688908
R. Chillarege
This paper uses four case studies to examine the difference in properties of Bohr-Mandel bugs. The mechanism used to differentiate Bohr versus Mandel bugs are the ODC Triggers that was developed in a previous study on this subject. In this study, the method is extended to reflect on two additional dimensions. First, on the customer perceived impact. And, second, on how these change between their manifestation in production or the field usage versus late stage development or quality assurance testing. This paper: ; Compares Bohr and Mandel bugs rates between customer/field usage and pre-release system testing. ; Finds that Mandel bugs predominantly have a Reliability-Availability-Serviceability (RAS) Impact. ; Finds that Mandel bugs, rarely, if ever have a Functional Impact. ; Finds these studies predict Mandel bug rates consistent with other studies. ; Finds that pre-release testing found very few Mandel bugs (<;10%).
{"title":"Comparing four case studies on Bohr-Mandel characteristics using ODC","authors":"R. Chillarege","doi":"10.1109/ISSREW.2013.6688908","DOIUrl":"https://doi.org/10.1109/ISSREW.2013.6688908","url":null,"abstract":"This paper uses four case studies to examine the difference in properties of Bohr-Mandel bugs. The mechanism used to differentiate Bohr versus Mandel bugs are the ODC Triggers that was developed in a previous study on this subject. In this study, the method is extended to reflect on two additional dimensions. First, on the customer perceived impact. And, second, on how these change between their manifestation in production or the field usage versus late stage development or quality assurance testing. This paper: ; Compares Bohr and Mandel bugs rates between customer/field usage and pre-release system testing. ; Finds that Mandel bugs predominantly have a Reliability-Availability-Serviceability (RAS) Impact. ; Finds that Mandel bugs, rarely, if ever have a Functional Impact. ; Finds these studies predict Mandel bug rates consistent with other studies. ; Finds that pre-release testing found very few Mandel bugs (<;10%).","PeriodicalId":332420,"journal":{"name":"2013 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115452636","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}
Pub Date : 2013-11-01DOI: 10.1109/ISSREW.2013.6688918
Lili Xu, Hong Zhang
An improved analysis process of software failure modes and effects analysis (SFMEA) is presented in this paper, to alleviate the difficulties and heavy workload while applying the conventional SFMEA approach to complex systems. By integrating SFMEA with the functional structure, data flow diagram (DFD), control flow diagram (CFD) and software fault tree analysis (SFTA), the proposed method is easier and more convenient to be carried out. At last, we took a fly-by-wire flight control system for case study to verify the feasibility of this approach. The case study shows that the improved SFMEA method can help save effort while analyzing complex systems.
{"title":"An improved SFMEA method integrated with assistive techniques","authors":"Lili Xu, Hong Zhang","doi":"10.1109/ISSREW.2013.6688918","DOIUrl":"https://doi.org/10.1109/ISSREW.2013.6688918","url":null,"abstract":"An improved analysis process of software failure modes and effects analysis (SFMEA) is presented in this paper, to alleviate the difficulties and heavy workload while applying the conventional SFMEA approach to complex systems. By integrating SFMEA with the functional structure, data flow diagram (DFD), control flow diagram (CFD) and software fault tree analysis (SFTA), the proposed method is easier and more convenient to be carried out. At last, we took a fly-by-wire flight control system for case study to verify the feasibility of this approach. The case study shows that the improved SFMEA method can help save effort while analyzing complex systems.","PeriodicalId":332420,"journal":{"name":"2013 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126665141","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}
Pub Date : 2013-11-01DOI: 10.1109/ISSREW.2013.6688882
K. Vinod, M. Ramachandra, S. Yalawar, Pandit Pattabhirama
With the advancement of analytical engines for big data, the healthcare industry has taken a big leap to minimize escalations on healthcare expenditure, while providing a reliably working solution for the customers based on the slice and dice of the collected information. The research and development (R & D) departments of the healthcare players are providing more focus on the stability and the usage of the system in the field. The field studies have created a reliability based feedback loop that has helped R & D provide hotfixes and service packs in shrinking time lines to better answer the customized needs of the user. Given the variety of possible optimizations in the actual usage, the software-hardware product combine such as the Philips Magnetic Resonance (MR) modality has to ensure that the business critical workflows are ever stable. In a nutshell, fault prediction becomes an important aspect for the R & D department because it helps address the situation in an effective and timely fashion, for both the end-user and the manufacturer to alleviate process hiccups and delays in addressing the fault. Reliability growth plot using the Weibull probability plots helps to predict failures that guide reliability centric maintenance strategies [1]; however, this will be a passive application of prediction for the new software yet to be released for market. This paper tries to address the case where a fault/failure at the customer-end can be better predicted for software-under-development with the help of analysis of field data. The terms failures and faults are interchangeably used in the paper to represent error events that can occur at an installed base.
随着大数据分析引擎的进步，医疗保健行业在最大限度地减少医疗保健支出升级方面取得了巨大飞跃，同时根据收集的信息的碎片为客户提供可靠的工作解决方案。医疗保健参与者的研究和开发(r&d)部门更加关注系统在现场的稳定性和使用。现场研究建立了一个基于可靠性的反馈回路，帮助研发部门在缩短的时间内提供修复程序和服务包，以更好地满足用户的定制需求。考虑到实际使用中可能的各种优化，软硬件产品组合(如Philips Magnetic Resonance (MR)模式)必须确保关键业务工作流始终稳定。简而言之，故障预测成为研发部门的一个重要方面，因为它可以帮助最终用户和制造商以有效和及时的方式解决问题，从而减轻解决故障时的过程中断和延迟。使用威布尔概率图的可靠性增长图有助于预测故障，从而指导以可靠性为中心的维护策略[1];然而，这将是一个被动的应用预测的新软件尚未发布市场。本文试图解决这样一种情况，即在现场数据分析的帮助下，客户端的故障/故障可以更好地预测正在开发的软件。术语“失败”和“故障”在本文中可以互换使用，以表示在安装基础上可能发生的错误事件。
{"title":"Diagnosing development software release to predict field failures","authors":"K. Vinod, M. Ramachandra, S. Yalawar, Pandit Pattabhirama","doi":"10.1109/ISSREW.2013.6688882","DOIUrl":"https://doi.org/10.1109/ISSREW.2013.6688882","url":null,"abstract":"With the advancement of analytical engines for big data, the healthcare industry has taken a big leap to minimize escalations on healthcare expenditure, while providing a reliably working solution for the customers based on the slice and dice of the collected information. The research and development (R & D) departments of the healthcare players are providing more focus on the stability and the usage of the system in the field. The field studies have created a reliability based feedback loop that has helped R & D provide hotfixes and service packs in shrinking time lines to better answer the customized needs of the user. Given the variety of possible optimizations in the actual usage, the software-hardware product combine such as the Philips Magnetic Resonance (MR) modality has to ensure that the business critical workflows are ever stable. In a nutshell, fault prediction becomes an important aspect for the R & D department because it helps address the situation in an effective and timely fashion, for both the end-user and the manufacturer to alleviate process hiccups and delays in addressing the fault. Reliability growth plot using the Weibull probability plots helps to predict failures that guide reliability centric maintenance strategies [1]; however, this will be a passive application of prediction for the new software yet to be released for market. This paper tries to address the case where a fault/failure at the customer-end can be better predicted for software-under-development with the help of analysis of field data. The terms failures and faults are interchangeably used in the paper to represent error events that can occur at an installed base.","PeriodicalId":332420,"journal":{"name":"2013 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW)","volume":"22 7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125609956","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}
Pub Date : 2013-11-01DOI: 10.1109/ISSREW.2013.6688910
Yukiko Yanagisawa, Takashi Ito, M. Takeyama, Y. Yokote
This paper proposes a V-model method to build consensus on dependability of the target system through collaborative construction of D-Case aligned with the organizational structure of stakeholders. D-Case is an extended assurance case supported by D-ADD agreement description database in the DEOS process for open systems dependability. The example target system here is Business Broadcasting System, the mission-critical system of commercial TV stations. We identify four issues in consensus building using D-Case and show how they are overcome using the functionality of D-ADD in our method: 1) Ensuring the integrity of D-Case, 2) Identifying the area affected by a D-Case modification, 3) Writing D-Case with multiple authors, and 4) Clarifying the scope of responsibility of each stakeholder.
{"title":"A new method of consensus building for open systems dependability","authors":"Yukiko Yanagisawa, Takashi Ito, M. Takeyama, Y. Yokote","doi":"10.1109/ISSREW.2013.6688910","DOIUrl":"https://doi.org/10.1109/ISSREW.2013.6688910","url":null,"abstract":"This paper proposes a V-model method to build consensus on dependability of the target system through collaborative construction of D-Case aligned with the organizational structure of stakeholders. D-Case is an extended assurance case supported by D-ADD agreement description database in the DEOS process for open systems dependability. The example target system here is Business Broadcasting System, the mission-critical system of commercial TV stations. We identify four issues in consensus building using D-Case and show how they are overcome using the functionality of D-ADD in our method: 1) Ensuring the integrity of D-Case, 2) Identifying the area affected by a D-Case modification, 3) Writing D-Case with multiple authors, and 4) Clarifying the scope of responsibility of each stakeholder.","PeriodicalId":332420,"journal":{"name":"2013 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121054414","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}
Pub Date : 1900-01-01DOI: 10.1109/issrew.2013.6688867
Automated code inspection using static analysis tools has been found to be useful and cost-effective over manual code reviews. This is due to ability of these tools to detect programming bugs (or defects) early in the software development cycle without running the code. Further, using sound static analysis tools, even large industry applications can be certified to be free of certain types of the programming bugs such as Division by Zero, Null/Illegal Dereference of a Pointer, Memory Leaks, and so on. In spite of these merits, as per various surveys, the static analysis tools are used infrequently and inconsistently in practice to ensure software quality. Large number of false alarms generated and the efforts required to manually analyze them are the primary reasons for this. Similar has been the experience of our team with the usage of these tools.
{"title":"Improving manual analysis of automated code inspection results: Need and effectiveness","authors":"","doi":"10.1109/issrew.2013.6688867","DOIUrl":"https://doi.org/10.1109/issrew.2013.6688867","url":null,"abstract":"Automated code inspection using static analysis tools has been found to be useful and cost-effective over manual code reviews. This is due to ability of these tools to detect programming bugs (or defects) early in the software development cycle without running the code. Further, using sound static analysis tools, even large industry applications can be certified to be free of certain types of the programming bugs such as Division by Zero, Null/Illegal Dereference of a Pointer, Memory Leaks, and so on. In spite of these merits, as per various surveys, the static analysis tools are used infrequently and inconsistently in practice to ensure software quality. Large number of false alarms generated and the efforts required to manually analyze them are the primary reasons for this. Similar has been the experience of our team with the usage of these tools.","PeriodicalId":332420,"journal":{"name":"2013 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130437617","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}
Pub Date : 1900-01-01DOI: 10.1109/issrew.2013.6688884
In this study, we focused on the process of upgrading software and analyzed the factors and influences that drove that adoption. An evaluation of adoption data of five major product families across three major industries and three operating systems revealed consistent upgrade patterns based on the type of product, its innovativeness, reliability and customer perception. Further investigation using a survey method of product engineers tasked with providing customer support for those products revealed similar patterns of the software upgrading behavior. If factors that impact software upgrading behavior are identified, they can be used as leading indicators of software adoption and suppliers of these upgrades may use this information to better plan software releases to optimize customer migration plans and improve Release cadence adjustments.
{"title":"Release cadence: A product software upgrade study","authors":"","doi":"10.1109/issrew.2013.6688884","DOIUrl":"https://doi.org/10.1109/issrew.2013.6688884","url":null,"abstract":"In this study, we focused on the process of upgrading software and analyzed the factors and influences that drove that adoption. An evaluation of adoption data of five major product families across three major industries and three operating systems revealed consistent upgrade patterns based on the type of product, its innovativeness, reliability and customer perception. Further investigation using a survey method of product engineers tasked with providing customer support for those products revealed similar patterns of the software upgrading behavior. If factors that impact software upgrading behavior are identified, they can be used as leading indicators of software adoption and suppliers of these upgrades may use this information to better plan software releases to optimize customer migration plans and improve Release cadence adjustments.","PeriodicalId":332420,"journal":{"name":"2013 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131766753","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}
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