Better defect detection and prevention through improved inspection and testing approach in small and medium scale software industry

Suma, V.; Nair, T. R. Gopalakrishnan

doi:10.1504/ijpqm.2010.033885

Cited by 13 publications

(8 citation statements)

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“…Managers get the added advantage of monitoring team performance, project after project in a convincing way using numerical estimations through characteristic coefficients of the team or the company using DI and IPM. DI, the process metric and IPM, the people metric with their nature of visibility enable the software organisation to achieve a reliable defect capturing capability [7,11].…”

Section: Discussionmentioning

confidence: 99%

“…In this situation, a clear-cut awareness of effort measurement enables the individual and team to perform to the desired levels of process quality and people quality. Therefore authors in [7] have introduced two quality metrics namely DI and IPM to measure the quality levels of inspection process and people performance [7,11]. They in [24] elucidate the uniqueness of their newly introduced pair metric with the already existing inspection related quality metrics.…”

Section: Background Workmentioning

confidence: 99%

“…This is a strong rationale for the software industries to equip themselves towards analytical mode of resource allocation for defect management in lieu of intuitive mode what currently exists. However, the recently introduced pair metrics enable the company now to estimate and predict accurately the required quality of inspection process and people performance through DI and IPM metrics, respectively [7,11]. Further, the defects captured by test team are very low at design phase when compared to the requirements analysis phase of development.…”

Section: Case Studiesmentioning

confidence: 99%

“…Let DI be the depth of inspection, N i be the number of defects captured by inspection process and T d be the number of defects captured by both inspection and testing approaches [11]. DI can be measured phase-wise or as a whole before the deployment of the product, using the metric (1) given below…”

Section: Introductionmentioning

confidence: 99%

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Significance of depth of inspection and inspection performance metrics for consistent defect management in software industry

2012

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Production of high-quality software is the exquisite need for accomplishing absolute customer satisfaction in software industry. Effective defect management is one of the crucial factors enabling successful development of high-quality products. Inspection and testing are two established methods of defect management domain. However, existing industry atmosphere is not stringent on the quantification of quality of process and people, in order to realise the prime objective of effective defect management. Consequently, defect capturing ability of the process and the efficacy of people are anecdotal leading towards defect manifestation and propagation during different software development stages. This study provides a case study involving empirical analysis of projects from a leading product-based software industry. The investigation strongly indicates the need for awareness and use of quality measurement of process and people in realising effective defect management. Implementation of two recently introduced quality metrics depth of inspection, a process metric and inspection performance metric, a people metric enable the developing team to generate high-quality software. The comprehension of these pair metrics in software development further augments the quality and productivity. It also reduces the expensive rework time, cost and rebinding of resources. Implementation of duo metrics reflects the persistent process improvement of the software enterprise and the resultant success.

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Section: Discussionmentioning

confidence: 99%

Section: Background Workmentioning

confidence: 99%

Section: Case Studiesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Significance of depth of inspection and inspection performance metrics for consistent defect management in software industry

2012

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“…Further, inspection and testing are deemed to be one of the effective modes of defect management [18], [19], [20], [21], [22]. Hence, in order to predict the success/failure of projects, this investigation led us to collect empirical data based on defect profiles.…”

Section: Methodsmentioning

confidence: 99%

An approach to predict software project success by cascading clustering and classification

Ramaswamy

Suma

Pushphavathi

2012

International Conference on Software Engineering and Mobile Application Modelling and Development (ICSEMA 2012)

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Generation of successful project is the core challenge of the day. Prediction of software project success is therefore one of the vital activities of software engineering community. Data mining techniques enable one to predict the success of the company by estimating the degree of success of their projects. This paper presents an empirical study of several projects developed at various software industries in order to comprehend the effectiveness of data mining technique for efficient project management. The paper provides K-means clustering approach for grouping of projects based on project success as one of the parameters. Subsequently, different classification algorithms are trained on the result set to build the classifier model based on K-fold cross validation. The best accuracy for the given dataset is achieved in Random Forest algorithm compared to other classifiers. This mode of project management using effective data mining techniques on empirical projects ensures accurate prediction of project success rate of the company. It further reflects process maturity leading towards implementation of strategies for improved productivity and sustainability of the company in the industrial market.

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Software Process Improvement Based on Defect Prevention Using Capability and Testing Model Integration in Extreme Programming

Rahman¹,

Rahman²,

Al-Mustanjid³

et al. 2020

Cyber Security and Computer Science

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Nowadays, Software Process Improvement popularly known as SPI has been able to receive an immense concern in the continuous process to purify software quality. Several Agile methodologies previously have worked with Extreme programming (XP). Before improving the process, defect prevention (DP) is inevitable. In addition, DP largely depends on defect detection either found earlier in the design and implementation stages or held in the testing phases. However, testing maturity model integration (TMMI) has a crucial aspect in DP as well as process improvement of the software. In particular, when software gets validated by being tested and fixed the defects up, it achieves the maximum capability maturity model integration (CMMI) aiming the process improvement. Here, the article has proposed an improved defect detection and prevention model to enhance the software process following the approach of XP. Besides, as a unique contribution, we have united the capability and testing model integration to ensure better SPI.

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Better defect detection and prevention through improved inspection and testing approach in small and medium scale software industry

Cited by 13 publications

References 0 publications

Significance of depth of inspection and inspection performance metrics for consistent defect management in software industry

Significance of depth of inspection and inspection performance metrics for consistent defect management in software industry

An approach to predict software project success by cascading clustering and classification

Software Process Improvement Based on Defect Prevention Using Capability and Testing Model Integration in Extreme Programming

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