A Light-Weight Defect Classification Scheme for Embedded Automotive Software and Its Initial Evaluation

Mellegård, Niklas; Staron, Miroslaw; Törner, Fredrik

doi:10.1109/issre.2012.15

Cited by 23 publications

(16 citation statements)

References 11 publications

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“…The reason for such anomalous observation is explainable based on the defect inflow data and characteristics of models. As it can be seen the inconsistency is significant mainly for Delayed and Inflection S-shaped models -this occurs for a reason; it has been demonstrated in earlier studies [33], [34] that defect inflow profile in automotive software projects often is characterized by presence of late defects. Late defects are not a standard characteristic of normal S-shaped curve which is based on inverted bell shaped inflow profile.…”

Section: B Which Srgms Have the Best Long Term Predictive Power?mentioning

confidence: 91%

Evaluating long-term predictive power of standard reliability growth models on automotive systems

Rana

Staron

Berger

et al. 2013

2013 IEEE 24th International Symposium on Software Reliability Engineering (ISSRE)

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Software is today an integral part of providing improved functionality and innovative features in the automotive industry. Safety and reliability are important requirements for automotive software and software testing is still the main source of ensuring dependability of the software artifacts. Software Reliability Growth Models (SRGMs) have been long used to assess the reliability of software systems; they are also used for predicting the defect inflow in order to allocate maintenance resources. Although a number of models have been proposed and evaluated, much of the assessment of their predictive ability is studied for short term (e.g. last 10% of data). But in practice (in industry) the usefulness of SRGMs with respect to optimal resource allocation depends heavily on the long term predictive power of SRGMs i.e. much before the project is close to completion. The ability to reasonably predict the expected defect inflow provides important insight that can help project and quality managers to take necessary actions related to testing resource allocation on time to ensure high quality software at the release. In this paper we evaluate the long-term predictive power of commonly used SRGMs on four software projects from the automotive sector. The results indicate that Gompertz and Logistic model performs best among the tested models on all fit criterias as well as on predictive power, although these models are not reliable for long-term prediction with partial data.

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Section: B Which Srgms Have the Best Long Term Predictive Power?mentioning

confidence: 91%

Evaluating long-term predictive power of standard reliability growth models on automotive systems

Rana

Staron

Berger

et al. 2013

2013 IEEE 24th International Symposium on Software Reliability Engineering (ISSRE)

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“…The current cloud system is an evolution of the previous work on ensuring information reliability done together with Ericsson [SM09a]. In this work we address the problems of ensuring that information is available throughout the enterprise and its understanding [KS02,SKT05,MS10,MST12].…”

Section: Related Workmentioning

confidence: 99%

Measurement-as-a-Service – A New Way of Organizing Measurement Programs in Large Software Development Companies

Staron

Meding

2015

Software Measurement

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Abstract. Modern software development companies focus on their primary business objectives, delivering customer value and customer satisfaction which often leads to prioritization of core business areas over such areas as measurement. Although the companies recognize the need and importance of software measurement, they often do not have the competence and/or time to focus on software measurement. In this paper we address the challenge of optimizing the measurement processes in modern companies by using cloud computing and by providing measurement (process) as a service for core business of the companies. Similar to the concept of Software-as-a-Service we define the concept Measurementas-a-Service and describe how to organize a measurement program according to this definition. The Measurement-as-a-Service concept is wellaligned with measurement programs developed according to ISO/IEC 15939 and can help the companies to increase the benefits obtained from the efficient use of metrics.

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“…There is a high percentage of not tried or not available cases, in which reporters did not care about this aspect or were not able to establish this value. 3 Considering that, in the literature, this type of defects are reported with percentages around 20-40%, even in critical contexts [23,24], the low percentage can be justified by the scarce focus on establishing if a defect is always reproducible or not. Although the testing phase is not the final one, and more bugs of this type are expected to surface in later stages, our conjecture is confirmed by the high percentage of not tried or not available cases.…”

Section: Fine-grain Analysismentioning

confidence: 99%

“…Oppositely, implementing classification schemes as ODC or HP yields much information on single‐phase efficiency but at higher expense and greater intrusiveness. Their application into real industrial settings can be difficult , because of start‐up costs (e.g., training and process changes), of required customizations (e.g. Ref.…”

Section: Introductionmentioning

confidence: 99%

“…schemes as ODC or HP yields much information on single-phase efficiency but at higher expense and greater intrusiveness. Their application into real industrial settings can be difficult [3,4], because of start-up costs (e.g., training and process changes), of required customizations (e.g. Ref.[5]), of nonimmediate visible gain and of reluctance of people to change their routine job.This article presents a study of defect analysis in the domain of mission-critical software systems aimed at evaluating the software development process with respect to the quality of produced software and its relation with the effort required to attain that quality.…”

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confidence: 99%

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Defect analysis in mission-critical software systems: a detailed investigation

Carrozza

Pietrantuono

Russo

2014

J. Softw. Evol. and Proc.

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The practice of defect analysis is recognized as an essential task for software process measurement, yet its\ud effective application in the industrial development of large-scale software systems raises several challenges.\ud We report the results of a study conducted at SELEX ES - a large system integrator leader in the market of\ud software-intensive mission-critical systems. The article describes the defect analysis approach that we tailored to evaluate the software development process with respect to the quality of produced software and\ud its relation with the required effort. Three key phases of the process were addressed, regarding the software\ud implementation, the testing phase and the prerelease defect fixing activity, over a set of six computer software configuration items developed from 2009 to 2012 for the naval and maritime domain product line.\ud The analysis highlighted efficiency bottlenecks in each of the monitored phases, providing company engineers with insights about room for process improvement. The implemented approach, the observed phenomena and the inferred conclusions are of support to practitioners coping with systems, development models and\ud industrial environments similar to the considered one

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A Light-Weight Defect Classification Scheme for Embedded Automotive Software and Its Initial Evaluation

Cited by 23 publications

References 11 publications

Evaluating long-term predictive power of standard reliability growth models on automotive systems

Evaluating long-term predictive power of standard reliability growth models on automotive systems

Measurement-as-a-Service – A New Way of Organizing Measurement Programs in Large Software Development Companies

Defect analysis in mission-critical software systems: a detailed investigation

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