Pub Date : 2013-12-19DOI: 10.1109/ISSREW.2013.6688880
Jinghui Li, Xuewen Gong, Jianqing Yuan
Summary form only given. Resource leaks are a common type of software fault. Accruing with time, resource leaks can lead to performance degradation and/or service failures. However, there are few effective general methods and tools to detect and especially predict resource leaks. We propose a lightweight statistical approach to tackling this problem. Without complex resource management and modification to the original application code, the proposed approach simply monitors the target's resource usage periodically, and exploits some statistical analysis methods to extract the useful information behind the usage data. The decomposition method from the field of time series analysis is adopted to identify the different components (trend, seasonal, and random) of resource usage. The Mann-Kendall test method is then applied to the decomposed trend component to identify whether a significant consistent upward trend exists (and thus a leak). Furthermore, we establish a prediction procedure based on the decomposition. The basic idea is to estimate the three different components separately (using such statistical methods as curve fitting and confidence limit), and then add them together to predict the total usage. Several experimental studies that take memory as an example resource demonstrate that our proposed approach is effective to detect leaks and predict relevant leak index of interest (e.g., time to exhaustion, time to crossing some dangerous threshold), and has a very low runtime overhead.
{"title":"A statistical approach for software resource leak detection and prediction","authors":"Jinghui Li, Xuewen Gong, Jianqing Yuan","doi":"10.1109/ISSREW.2013.6688880","DOIUrl":"https://doi.org/10.1109/ISSREW.2013.6688880","url":null,"abstract":"Summary form only given. Resource leaks are a common type of software fault. Accruing with time, resource leaks can lead to performance degradation and/or service failures. However, there are few effective general methods and tools to detect and especially predict resource leaks. We propose a lightweight statistical approach to tackling this problem. Without complex resource management and modification to the original application code, the proposed approach simply monitors the target's resource usage periodically, and exploits some statistical analysis methods to extract the useful information behind the usage data. The decomposition method from the field of time series analysis is adopted to identify the different components (trend, seasonal, and random) of resource usage. The Mann-Kendall test method is then applied to the decomposed trend component to identify whether a significant consistent upward trend exists (and thus a leak). Furthermore, we establish a prediction procedure based on the decomposition. The basic idea is to estimate the three different components separately (using such statistical methods as curve fitting and confidence limit), and then add them together to predict the total usage. Several experimental studies that take memory as an example resource demonstrate that our proposed approach is effective to detect leaks and predict relevant leak index of interest (e.g., time to exhaustion, time to crossing some dangerous threshold), and has a very low runtime overhead.","PeriodicalId":332420,"journal":{"name":"2013 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW)","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121809325","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 : 2013-12-19DOI: 10.1109/ISSREW.2013.6688885
Pete Rotella, Devesh Goyal, S. Chulani
Since 2009, Software Defects Per Million Hours (SWDPMH) has been the primary customer experience metric used at Cisco, and is goaled on a yearly basis for about 100 product families. A key reason SWDPMH is considered to be of critical importance is that we see a high correlation between SWDPMH and Software Customer Satisfaction (SW CSAT) over a wide spectrum of products and feature releases. Therefore, it is important to try to anticipate SWDPMH for new releases before the software is released to customers, for several reasons: · Early warning that a major feature release is likely to experience substantial quality problems in the field may allow for remediation of the release during, or even prior to, function and system testing · Prediction of SWDPMH enables better planning for subsequent maintenance releases and rollout strategies · Calculating the tradeoffs between SWDPMH and feature volume can provide guidance concerning acceptable feature content, test effort, release cycle timing, and other key parameters affecting subsequent feature releases. Our efforts over the past year have been to enhance our ability to predict SWDPMH in the field. Toward this end, we have developed predictive models, tested the models with major feature releases for strategic products, and provided guidance to development, test, and release management teams on how to improve the chances of achieving best-in-class levels of SWDPMH. This work is ongoing, but several models are currently used in a production mode for five product families, with good results. We plan to achieve production capability with an additional several dozen product families over the next year.
{"title":"Predicting field experience of releases on specific platforms","authors":"Pete Rotella, Devesh Goyal, S. Chulani","doi":"10.1109/ISSREW.2013.6688885","DOIUrl":"https://doi.org/10.1109/ISSREW.2013.6688885","url":null,"abstract":"Since 2009, Software Defects Per Million Hours (SWDPMH) has been the primary customer experience metric used at Cisco, and is goaled on a yearly basis for about 100 product families. A key reason SWDPMH is considered to be of critical importance is that we see a high correlation between SWDPMH and Software Customer Satisfaction (SW CSAT) over a wide spectrum of products and feature releases. Therefore, it is important to try to anticipate SWDPMH for new releases before the software is released to customers, for several reasons: · Early warning that a major feature release is likely to experience substantial quality problems in the field may allow for remediation of the release during, or even prior to, function and system testing · Prediction of SWDPMH enables better planning for subsequent maintenance releases and rollout strategies · Calculating the tradeoffs between SWDPMH and feature volume can provide guidance concerning acceptable feature content, test effort, release cycle timing, and other key parameters affecting subsequent feature releases. Our efforts over the past year have been to enhance our ability to predict SWDPMH in the field. Toward this end, we have developed predictive models, tested the models with major feature releases for strategic products, and provided guidance to development, test, and release management teams on how to improve the chances of achieving best-in-class levels of SWDPMH. This work is ongoing, but several models are currently used in a production mode for five product families, with good results. We plan to achieve production capability with an additional several dozen product families over the next year.","PeriodicalId":332420,"journal":{"name":"2013 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127853571","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 : 2013-12-19DOI: 10.1109/ISSREW.2013.6688871
S. Meena, Uma M. Balasubramani
Summary form only given. Defect classification plays a major role in categorizing the defects based on components, sub components, different product areas etc. A well defined defects classification mechanism is a base for any type of defect analysis. Defects can be classified based on tags. These tags can be user-defined, shared or personal tags related to any area in a product. Tags can be used for searching the work items and viewing the tagged artifacts. Tags are very easy to create but yet very helpful in categorizing the defects for analysis. Tags are generally used for very specific, detailed defect analysis. During the product implementation, we have used this tagging mechanism extensively which helped us analyzing the defects for better product stability, better performance, focusing on specific areas that needs improvement in the product. We created filter for the tags and saved that view in the project dashboard for quick analysis. We also used the defect view to create a tag cloud which displays the number of work items by tag attribute. In this article, we would show how to use tags effectively and write query with tag attribute for filtering of defects in specific areas in a product. Upon analyzing these tags we found some interesting issues in the product. In this paper, we will show defect categorization using tag cloud in a dynamic way. We will also present how tag cloud provides details of the defect based on importance and number of occurrences. The defect analysis also highlighted some components which needed more attention.
{"title":"Smart defect classification for better analysis using tagging mechanisms","authors":"S. Meena, Uma M. Balasubramani","doi":"10.1109/ISSREW.2013.6688871","DOIUrl":"https://doi.org/10.1109/ISSREW.2013.6688871","url":null,"abstract":"Summary form only given. Defect classification plays a major role in categorizing the defects based on components, sub components, different product areas etc. A well defined defects classification mechanism is a base for any type of defect analysis. Defects can be classified based on tags. These tags can be user-defined, shared or personal tags related to any area in a product. Tags can be used for searching the work items and viewing the tagged artifacts. Tags are very easy to create but yet very helpful in categorizing the defects for analysis. Tags are generally used for very specific, detailed defect analysis. During the product implementation, we have used this tagging mechanism extensively which helped us analyzing the defects for better product stability, better performance, focusing on specific areas that needs improvement in the product. We created filter for the tags and saved that view in the project dashboard for quick analysis. We also used the defect view to create a tag cloud which displays the number of work items by tag attribute. In this article, we would show how to use tags effectively and write query with tag attribute for filtering of defects in specific areas in a product. Upon analyzing these tags we found some interesting issues in the product. In this paper, we will show defect categorization using tag cloud in a dynamic way. We will also present how tag cloud provides details of the defect based on importance and number of occurrences. The defect analysis also highlighted some components which needed more attention.","PeriodicalId":332420,"journal":{"name":"2013 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW)","volume":"365 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124589949","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 : 2013-12-19DOI: 10.1109/ISSREW.2013.6688873
Aline Cristine Fadel, Regina L. O. Moraes, Paulo S. Martins, E. Martins
This paper presents the automation of a Gigabit Passive Optical Network (GPON) embedded software validation, which improves the coverage of tests and eliminates faults that may compromise system availability. A fault injection (FI) campaign based on a state machine model was performed emulating physical faults that automatically break down the communication between GPON network devices. Consequently, new failures were disclosed even after one-and-a-half year period using conventional test techniques.
{"title":"Automating software validation of a GPON network","authors":"Aline Cristine Fadel, Regina L. O. Moraes, Paulo S. Martins, E. Martins","doi":"10.1109/ISSREW.2013.6688873","DOIUrl":"https://doi.org/10.1109/ISSREW.2013.6688873","url":null,"abstract":"This paper presents the automation of a Gigabit Passive Optical Network (GPON) embedded software validation, which improves the coverage of tests and eliminates faults that may compromise system availability. A fault injection (FI) campaign based on a state machine model was performed emulating physical faults that automatically break down the communication between GPON network devices. Consequently, new failures were disclosed even after one-and-a-half year period using conventional test techniques.","PeriodicalId":332420,"journal":{"name":"2013 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125465523","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 : 2013-12-19DOI: 10.1109/ISSREW.2013.6688920
Michael Roth, P. Liggesmeyer
For the certification of modern safety critical systems tree based failure models, like standardized fault trees (FTs), are frequently used methodologies. But when it comes to software-intensive systems these techniques have some crucial disadvantages, especially in modeling timing behavior. To deal with these weak points state/event fault trees (SEFTs) [6] were developed. However, these kind of fault trees can only be analyzed in a quantitative way. In this paper we propose an approach to analyze them qualitatively as well. This results in ordered event sequences which represent different ways for triggering a critical event of the underlying SEFTs, which can be seen as a time-dependent equivalent of the minimal cut set (MCS) analysis of standardized FTs. To evaluate our approach, we implemented the SEFTAnalyzer to apply it on a software-controlled fire alert system.
{"title":"Qualitative analysis of state/event fault trees for supporting the certification process of software-intensive systems","authors":"Michael Roth, P. Liggesmeyer","doi":"10.1109/ISSREW.2013.6688920","DOIUrl":"https://doi.org/10.1109/ISSREW.2013.6688920","url":null,"abstract":"For the certification of modern safety critical systems tree based failure models, like standardized fault trees (FTs), are frequently used methodologies. But when it comes to software-intensive systems these techniques have some crucial disadvantages, especially in modeling timing behavior. To deal with these weak points state/event fault trees (SEFTs) [6] were developed. However, these kind of fault trees can only be analyzed in a quantitative way. In this paper we propose an approach to analyze them qualitatively as well. This results in ordered event sequences which represent different ways for triggering a critical event of the underlying SEFTs, which can be seen as a time-dependent equivalent of the minimal cut set (MCS) analysis of standardized FTs. To evaluate our approach, we implemented the SEFTAnalyzer to apply it on a software-controlled fire alert system.","PeriodicalId":332420,"journal":{"name":"2013 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122365015","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 : 2013-12-19DOI: 10.1109/ISSREW.2013.6688861
E. Verhulst, B. Sputh
Safety engineering standards define rigorous and controllable processes for system development. Nevertheless, safety standards differences from distinct domains are non-negligible. We focus in particular on the aviation, automotive and railway standards, all related to the transportation market. We argue that the Safety Integrity Levels are not sufficient to be used as a top level requirement for developing a safety critical system. We argue that Quality of Service is a more generic criterion that takes the trustworthiness as perceived by users into deeper account. In addition safety engineering standards provide very little guidance on how to compose safe systems from components, while this is the established engineering practice. We develop a novel normative concept called Assured Reliability and Resilience Level as a criterion that takes the industrial practice into account and show how it complements the Safety Integrity Level concept. An important difference is that it requires a component to carry a contract and the supporting evidence. ARRL can make a significant contribution to foster cross-domain safety engineering.
{"title":"ARRL: A criterion for compositional safety and systems engineering: A normative approach to specifying components","authors":"E. Verhulst, B. Sputh","doi":"10.1109/ISSREW.2013.6688861","DOIUrl":"https://doi.org/10.1109/ISSREW.2013.6688861","url":null,"abstract":"Safety engineering standards define rigorous and controllable processes for system development. Nevertheless, safety standards differences from distinct domains are non-negligible. We focus in particular on the aviation, automotive and railway standards, all related to the transportation market. We argue that the Safety Integrity Levels are not sufficient to be used as a top level requirement for developing a safety critical system. We argue that Quality of Service is a more generic criterion that takes the trustworthiness as perceived by users into deeper account. In addition safety engineering standards provide very little guidance on how to compose safe systems from components, while this is the established engineering practice. We develop a novel normative concept called Assured Reliability and Resilience Level as a criterion that takes the industrial practice into account and show how it complements the Safety Integrity Level concept. An important difference is that it requires a component to carry a contract and the supporting evidence. ARRL can make a significant contribution to foster cross-domain safety engineering.","PeriodicalId":332420,"journal":{"name":"2013 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128290797","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 : 2013-12-19DOI: 10.1109/ISSREW.2013.6688906
S. Ballerini, L. Carnevali, Marco Paolieri, Kumiko Tadano, F. Machida
When software contains aging-related faults and the system has a long mission period, phased-mission systems consisting of several software components can suffer from software aging, which is a progressive degradation of the software execution environment. Failures caused by software aging might impact on the mission success probability. In this paper, we present a model for a phased-mission system with software rejuvenation, and analyze the impacts of software rejuvenation on the success probability and completion time distribution of the mission. The mission of Mars exploration rover is considered as an example of phased-mission system. The analysis results show that the mission success probability is improved by software rejuvenation at the cost of the mission completion time.
{"title":"Software rejuvenation impacts on a phased-mission system for Mars exploration","authors":"S. Ballerini, L. Carnevali, Marco Paolieri, Kumiko Tadano, F. Machida","doi":"10.1109/ISSREW.2013.6688906","DOIUrl":"https://doi.org/10.1109/ISSREW.2013.6688906","url":null,"abstract":"When software contains aging-related faults and the system has a long mission period, phased-mission systems consisting of several software components can suffer from software aging, which is a progressive degradation of the software execution environment. Failures caused by software aging might impact on the mission success probability. In this paper, we present a model for a phased-mission system with software rejuvenation, and analyze the impacts of software rejuvenation on the success probability and completion time distribution of the mission. The mission of Mars exploration rover is considered as an example of phased-mission system. The analysis results show that the mission success probability is improved by software rejuvenation at the cost of the mission completion time.","PeriodicalId":332420,"journal":{"name":"2013 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125504710","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 : 2013-12-19DOI: 10.1109/ISSREW.2013.6688895
M. Ghanavati, A. Andrzejak, Zhen Dong
Despite of indisputable progress, automated debugging methods still face difficulties in terms of scalability and runtime efficiency. To reach large-scale projects, we propose an approach which reports small sets of suspicious code changes. Its essential strength is that size of these reports is proportional to the amount of changes between code commits, and not the total project size. In our method we combine version comparison and information on failed tests with static and dynamic analysis. We evaluate our method on real bugs from Apache Hadoop, an open source project with over 2 million LOC1. In 2 out of 4 cases, the set of suspects produced by our approach contains exactly the location of the defective code (and no false positives). Another defect could be pinpointed by small approach extensions. Moreover, the time overhead of our approach is moderate, namely 3-4 times the duration of a failed software test.
{"title":"Scalable isolation of failure-inducing changes via version comparison","authors":"M. Ghanavati, A. Andrzejak, Zhen Dong","doi":"10.1109/ISSREW.2013.6688895","DOIUrl":"https://doi.org/10.1109/ISSREW.2013.6688895","url":null,"abstract":"Despite of indisputable progress, automated debugging methods still face difficulties in terms of scalability and runtime efficiency. To reach large-scale projects, we propose an approach which reports small sets of suspicious code changes. Its essential strength is that size of these reports is proportional to the amount of changes between code commits, and not the total project size. In our method we combine version comparison and information on failed tests with static and dynamic analysis. We evaluate our method on real bugs from Apache Hadoop, an open source project with over 2 million LOC1. In 2 out of 4 cases, the set of suspects produced by our approach contains exactly the location of the defective code (and no false positives). Another defect could be pinpointed by small approach extensions. Moreover, the time overhead of our approach is moderate, namely 3-4 times the duration of a failed software test.","PeriodicalId":332420,"journal":{"name":"2013 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117236878","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 : 2013-12-19DOI: 10.1109/ISSREW.2013.6688865
R. Gupta
Application involved in data protection for enterprises are responsible to ensure data integrity on backup target as well as remote site designed for disaster recovery (DR). By nature, backup applications needs to operate under very infrastructure which are prone to multiple failure right from physical to application layers. If applications are not designed to consider its operating environment effectively they may not respond to fault in operating environment and may result in data loss and data unavailability scenario. They could potential lead into false reporting which later can become issue with data integrity. We at EMC applied multilayered fault injection test strategy for backup product where we identified different layers of product operating environments. The interface between two layers was targeted to inject appropriate fault based on role and functionality of these layers. The response of application and its impact to product behavior was monitored and analyzed. This has helped improving various exception handling, product agility to fault operating environment and improving usability by providing better picture on failure in product. This session can help audience on understanding how an application operating environments plays key role in designing test strategy. This leads into improving product reliability and better customer experience about application.
{"title":"Improving reliability of data protection software with integrated multilayered fault Injection testing","authors":"R. Gupta","doi":"10.1109/ISSREW.2013.6688865","DOIUrl":"https://doi.org/10.1109/ISSREW.2013.6688865","url":null,"abstract":"Application involved in data protection for enterprises are responsible to ensure data integrity on backup target as well as remote site designed for disaster recovery (DR). By nature, backup applications needs to operate under very infrastructure which are prone to multiple failure right from physical to application layers. If applications are not designed to consider its operating environment effectively they may not respond to fault in operating environment and may result in data loss and data unavailability scenario. They could potential lead into false reporting which later can become issue with data integrity. We at EMC applied multilayered fault injection test strategy for backup product where we identified different layers of product operating environments. The interface between two layers was targeted to inject appropriate fault based on role and functionality of these layers. The response of application and its impact to product behavior was monitored and analyzed. This has helped improving various exception handling, product agility to fault operating environment and improving usability by providing better picture on failure in product. This session can help audience on understanding how an application operating environments plays key role in designing test strategy. This leads into improving product reliability and better customer experience about application.","PeriodicalId":332420,"journal":{"name":"2013 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW)","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133982596","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 : 2013-12-19DOI: 10.1109/ISSREW.2013.6688862
R. Chillarege
This paper presents a case study using Orthogonal Defect Classification (ODC) as a diagnostic tool to understand the quality and productivity issues in a Agile enterprise web development project. The project spanned a little over two years and had an effort in the range of 100,000 hours. The use of Agile was new to this engineering team. However, the senior people in the team had several years of experience with different process models. The project used a Scrum development model and ran three week Sprints. The objective of the ODC analysis was to understand the dynamics of the development as it actually occurred - as opposed to what was on paper or believed to have been implemented. We also wanted to understand the quality of the product produced, its stability and causes of customer pain. The development process had a separate Quality Assurance (QA) function, and a development led test and inspection effort. We wanted to understand their individual effectiveness, and how the structure effected production level quality. This case study was conducted by the senior engineering team along with ODC expertise from our firm. A subset of the application (around 4 major components) were chosen for this study. This allowed for an examination of component level issues, versus systemic issues across the entire application.
{"title":"Using ODC to diagnose an Agile enterprise application development project","authors":"R. Chillarege","doi":"10.1109/ISSREW.2013.6688862","DOIUrl":"https://doi.org/10.1109/ISSREW.2013.6688862","url":null,"abstract":"This paper presents a case study using Orthogonal Defect Classification (ODC) as a diagnostic tool to understand the quality and productivity issues in a Agile enterprise web development project. The project spanned a little over two years and had an effort in the range of 100,000 hours. The use of Agile was new to this engineering team. However, the senior people in the team had several years of experience with different process models. The project used a Scrum development model and ran three week Sprints. The objective of the ODC analysis was to understand the dynamics of the development as it actually occurred - as opposed to what was on paper or believed to have been implemented. We also wanted to understand the quality of the product produced, its stability and causes of customer pain. The development process had a separate Quality Assurance (QA) function, and a development led test and inspection effort. We wanted to understand their individual effectiveness, and how the structure effected production level quality. This case study was conducted by the senior engineering team along with ODC expertise from our firm. A subset of the application (around 4 major components) were chosen for this study. This allowed for an examination of component level issues, versus systemic issues across the entire application.","PeriodicalId":332420,"journal":{"name":"2013 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123742390","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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