NDLI: Influencing factors of defect removal: an empirical study based on industrial data

Please wait, while we are loading the content...

Synthesizing evidence in software engineering research

Understanding the impact of code and process metrics on post-release defects: a case study on the Eclipse project

Object oriented design pattern decay: a taxonomy

Test case selection and prioritization: risk-based or design-based?

Transition from a plan-driven process to Scrum: a longitudinal case study on software quality

An empirical study of specification by example in a software engineering tool

Evaluating a model of software managers' information needs: an experiment

The effects of neuroticism on pair programming: an empirical study in the higher education context

Introducing the evaluation of complexity in functional size measurement: a UML-based approach

Gender differences and programming environments: across programming populations

Data accumulation and software effort prediction

Predicting OSS trustworthiness on the basis of elementary code assessment

The influence of environmental parameters on concurrency fault exposures: an exploratory study

Obtaining valid safety data for software safety measurement and process improvement

A controlled experiment for assessing the contribution of design pattern documentation on software maintenance

EXPRE: a repository for managing software data and experience

Can we evaluate the quality of software engineering experiments?

An effective fault aware test case prioritization by incorporating a fault localization technique

Building empirical support for automated code smell detection

An empirical investigation into a large-scale Java open source code repository

Are developers complying with the process: an XP study

On the effectiveness of screen mockups in requirements engineering: results from an internal replication

Utilizing GQM+Strategies for business value analysis: an approach for evaluating business goals

Trust dynamics in global software engineering

Categorization of real-time software components for code size estimation

A qualitative study of animation programming in the wild

Stakeholder perceptions of software project outcomes: an industry case study

An empirical study on the relationship between the use of agile practices and the success of Scrum projects

Evaluation of optimized staffing for feature development and bug fixing

Impact analysis by means of unstructured knowledge in the context of bug repositories

Comparing two communication media in use case modeling: results from a controlled experiment

Agile security issues: an empirical study

Replications types in experimental disciplines

A machine learning approach for text categorization of fixing-issue commits on CVS

Strengthening the empirical analysis of the relationship between Linus' Law and software security

A survey of scientific software development

Perceived productivity threats in large agile development projects

A comprehensive characterization of NLP techniques for identifying equivalent requirements

Improving industrial adoption of software engineering research: a comparison of open and closed source software

Investigating the use of tags in collaborative development environments: a replicated study

Evaluating the suitability of a measurement repository for statistical process control

Usability evaluation of multi-device/platform user interfaces generated by model-driven engineering

A critical appraisal of systematic reviews in software engineering from the perspective of the research questions asked in the reviews

Using virtual machines for collaborative research

A focus group study on inter-organizational ERP requirements engineering practices

The usual suspects: a case study on delivered defects per developer

Towards to the validation of a usability evaluation method for model-driven web development

Detecting missing thrown exceptions in enterprise systems: an empirical study

Towards the conception of scientific workflows for in silico experiments in software engineering

A conceptual model of client-driven agile requirements prioritization: results of a case study

Continued involvement in software development: motivational factors

Evaluating the usefulness of a functional size measurement procedure to detect defects in MDD models

Are Heroes common in FLOSS projects?

Characteristics of high performing testers: a case study

Exploring the use of crowdsourcing to support empirical studies in software engineering

On the effort of augmenting use cases with screen mockups: results from a preliminary empirical study

Is GQM+Strategies really applicable as is to non-software development domains?

Impact of maintainability defects on code inspections

Adaptability performance trade-off: a controlled experiment

Applying MDA to complex multi-tier enterprise architectures

Impact analysis of SCRs using single and multi-label machine learning classification

Effects of the number of developers on code quality in open source software: a case study

CodeVizard: a tool to aid the analysis of software evolution

Traceable complexity metric from requirements to code

An event-based empirical process analysis framework

Influencing factors of defect removal: an empirical study based on industrial data

Quantitative software security measurement in an engineering service bus platform

Preliminary analysis of the effects of confirmation bias on software defect density

Influencing factors of defect removal: an empirical study based on industrial data

Content Provider	ACM Digital Library
Author	Hu, Chenyong Wang, Dandan Yang, Ye Wang, Qing
Abstract	Software testing is an important process for software quality control, and it is also costly and time-consuming. It can easily take 50% of development time [1]. To gain high quality software, a frequently-adopted approach is to try to minimize the number of defects in the final product, and it depends on software testing effectiveness. Many studies show that testing process is among one of the most difficult management practices. It is the last step to remove the defects before the software product to be released. But how to evaluate the quality of testing, a common way is to measure the defects detected during testing. When a defect was detected, if we can know the probability of the defect can be fixed, we can economize the limited time to fix more defects. But how we know the defect can be fixed or not before fixing. In our study, we want to find out which factors affect the defect removal. Whether the defects can be removed may be affected by many factors, for example, the engineers' experience, the defect severity, and the quality of modules that the defects belonged to. In this study, we only analyzed these three factors. a. The engineers' experience. In the testing process, the personnel capability and experience of the people involved is important factor not only for defects detected but also for the defects removal. The experience of a person can reflect his proficiency in defects detected or defects removal, it can reflected the capability of the person to a certain extent. In the datasets we used, the engineer that be assigned a defect is the programmer who is responsible to the code that produce the defect. b. The defect severity. It is one of important attributes for defects. It can reflect the degree of the risk or damage for software. In general, a defect has the more severe will have a greater probability to be removed. c. The quality of modules. In this study, we only considered the number of detected defects as an indicator for the quality of modules. We use ratio of defect removal as major indicator, analyze "which factors have impact on the defect removal?" This question can be split into the following three specific research questions: RQ1: Fixing defect is a human intensive activity, whether engineers' experience has significant impact on the defect removal? RQ2: Regarding the defect severity, whether the different severity has significant difference for the ratio of defect removal? And does the defect severity affect the results in RQ1? RQ3: Regarding the software module, size, complexity and quality are used to measure the module. Whether its difference has significant difference for the ratio of defect removal? And does it affect the results in RQ1? Aiming at investigating the influencing factors of defect removal with three factors: engineers' experience, defect severity and quality of modules, we got data from ten industrial test projects, which executed system testing for five embedded software products and their ten versions, and we gain the following three findings: a. Engineers' experience has significant impact on RODR. Usually it is said the more experience will have better defect removal. But our case showed a contrary finding. Multiple factors mixture analysis looks more benefit. b. The higher severity defects have a higher RODR. Combine with experience, in most severity the more engineers' experience, the higher the RODR. And the range of RODR for EY3 is quite lager. Probably, it is why the lower average of RODR in this level. The quality of modules has impact on RODR, but it is quite different in each quality level. In MC2 and MC3, the modules have more defect, we assume they will have more complexity and lower quality. The average of RODR descended with the experience increase and the range is quite large. The project managers said the skilled engineers were assigned to complex module. The more complexity defect, the more difficult to be fixed. It is why the lower defect removal. But the large range means the performance of engineers is not consistent even though they are in the same level. It will be a meaningful improvement point.
Starting Page	1
Ending Page	1
Page Count	1
File Format	PDF
ISBN	9781450300391
DOI	10.1145/1852786.1852868
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2010-09-16
Publisher Place	New York
Access Restriction	Subscribed
Content Type	Text
Resource Type	Article

Central Library (ISO-9001:2015 Certified)
Indian Institute of Technology Kharagpur
Kharagpur, West Bengal, India | PIN - 721302

See location in the Map
03222 282435
Mail: support@ndl.gov.in

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in