Metrics for small projects: Experiences at the SED

Grable, Ross; Jernigan, J. G.; Pogue, Chris; Divis, D.

doi:10.1109/52.754048

Cited by 18 publications

(22 citation statements)

References 2 publications

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“…We did not identify any study with the product perspective alone within the established SPI framework category; however rows A, B, E, F and G in Table 12 show that it is common to combine the project and product perspectives. [130], [135], [146], [148], [151], [152], [169], [170], [204], [206], [227], [229], [231], [233], [234] - [184] [121], [129], [145], [189], [207], [249], [262] [186] - [177], [193], [219] B CMMI [178], [265] -…”

Section: Resultsmentioning

confidence: 99%

“…[121], [127], [128], [136], [145], [147], [150], [152], [159], [165], [167], [169], [174], [180], [183], [188], [190], [191], [195], [197], [204], [208], [216], [219], [227], [229]- [231], [240], [242], [244], [247]- [249], [251], [253], [256], [257], [259], [261], [265] 41 Defects This success indicator is to group metrics that are solely intended to measure the defects without relating them to quality.…”

Section: Analysis and Discussionmentioning

confidence: 99%

“…Estimation accuracy: In Table 11 the success indicators for estimation accuracy are shown. It is interesting that estimating quality seems very uncommon although the improvement of quality is one of the main interests of [122], [143], [144], [149], [153], [154], [157], [159], [161], [163], [167], [169], [172], [177], [178], [183], [185], [186], [189], [191], [194], [195], [211], [219], [221], [225], [226], [237], [238], [240], [251], [256], [257], [262], [265], [266] 37/0.66…”

Section: Analysis and Discussionmentioning

confidence: 99%

“…[121], [135], [139], [143], [144], [150], [152], [156], [159], [162]- [164], [168], [169], [173], [179], [181], [182], [186], [190], [205], [208], [212], [215], [219], [221], [224], [227], [231], [239], [242], [246], [251], [257], [265] 35 mapped the improvement goals of quality, cost and schedule with these success indicators:…”

Section: Analysis and Discussionmentioning

confidence: 99%

“…[119]- [122], [125], [136], [139]- [141], [143], [144], [149], [152]- [154], [157], [159]- [161], [163], [167], [169], [170], [172], [176]- [178], [183], [185]- [187], [189], [191], [194], [195], [204]- [206], [211], [219], [221], [222], [225]- [227], [229], [237], [238], [240], [243], [255]- [257], [262], [265], [266] 56 Productivity The performance of the development team in terms of its efficiency in delivering the required output.…”

Section: Analysis and Discussionmentioning

confidence: 99%

See 4 more Smart Citations

Evaluation and Measurement of Software Process Improvement—A Systematic Literature Review

Unterkalmsteiner

Gorschek

Islam

et al. 2012

IIEEE Trans. Software Eng.

244

147

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BACKGROUND-Software Process Improvement (SPI) is a systematic approach to increase the efficiency and effectiveness of a software development organization and to enhance software products. OBJECTIVE-This paper aims to identify and characterize evaluation strategies and measurements used to assess the impact of different SPI initiatives. METHOD-The systematic literature review includes 148 papers published between 1991 and 2008. The selected papers were classified according to SPI initiative, applied evaluation strategies and measurement perspectives. Potential confounding factors interfering with the evaluation of the improvement effort were assessed. RESULTS-Seven distinct evaluation strategies were identified, whereas the most common one, "Pre-Post Comparison", was applied in 49% of the inspected papers. Quality was the most measured attribute (62%), followed by Cost (41%) and Schedule (18%). Looking at measurement perspectives, "Project" represents the majority with 66%. CONCLUSION-The evaluation validity of SPI initiatives is challenged by the scarce consideration of potential confounding factors, particularly given that "Pre-Post Comparison" was identified as the most common evaluation strategy, and the inaccurate descriptions of the evaluation context. Measurements to assess the short and mid-term impact of SPI initiatives prevail, whereas long-term measurements in terms of customer satisfaction and return on investment tend to be less used.

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Section: Resultsmentioning

confidence: 99%

Section: Analysis and Discussionmentioning

confidence: 99%

Section: Analysis and Discussionmentioning

confidence: 99%

Section: Analysis and Discussionmentioning

confidence: 99%

Section: Analysis and Discussionmentioning

confidence: 99%

See 3 more Smart Citations

Evaluation and Measurement of Software Process Improvement—A Systematic Literature Review

Unterkalmsteiner

Gorschek

Islam

et al. 2012

IIEEE Trans. Software Eng.

244

147

View full text Add to dashboard Cite

show abstract

Verification and validation of operational software: a process and methodology critique

Arthur

Gröner

2004

Softw Process Imprv Pract

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Verification and Validation (V&V) play a crucial role in producing a quality product on time, within budget and within scope. In this article, we examine the effectiveness of the Software Engineering Evaluation System (SEES), a V&V methodology developed by the U.S. Army Software Engineering Directorate. The critique draws on experiences and insights stemming from an application of that methodology to a controlled software development effort. In addition to citing the beneficial activities mandated by the V&V methodology, we also provide a discussion of prescribed (or lacking) activities having an adverse impact on the V&V effort. Recommendations to improve V&V effectiveness are also presented. Although our discussion focuses on V&V activities defined by the Army's methodology, the insights, lessons learned, and suggested improvements are widely applicable to the more generalized approaches to V&V. Copyright © 2004 John Wiley & Sons, Ltd.

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