Abstract 20 century end, the third wave democratization wave tide cause the snowballing effects, lead to the former Soviet Union and Eastern Europe communist nation disintegration and walk the road that democracy transform. The Mainland China nature receives to relatively big impact, especially U.S¡Bformer Soviet Union the breakup of two very confrontation systems, make the western nation as to it¡¦s the military strategy and western value a victory of peaceful evolution believe deeply to do not move, cause the western nation more do not accept China domestic human rights to record not good. Under the effort of United Nations, the convenant of international human rights have become the human the lowest human rights standard possessed of 21 century, differ from the PRC regime words is a new imperialism to the China sovereignty of interfere with. The research believes at the world widespread acceptance democracy and human rights value, China will increase to the possibility that democracy transform.

Context: Despite continuously increasing importance of Agile and Lean in software development, the number of studies that investigate on use of metrics relevant to Agile or Lean are limited and yet few studies implements was unclear. Unclear is which are the prominent metrics that are useful in industries, and their purpose of usage. Objectives: Main goal of this study is to find the metrics useful in Agile and Lean practicing industries; that are evaluated in industries by systematically identifying all the metrics from empirical evidence found in Literature as well as verifying which of them are prominently being used in industries. In addition, the purpose of using these metrics in industries are reported, and causes for dissatisfaction on use of some of the identified metrics among surveyed companies are investigated and reported. Methods: Two research methodologies are used; Systematic Literature Review (SLR) and Industrial Survey. SLR is performed using snowballing as search approach to select primary studies. SLR is used to identify all the metrics that are useful for Agile and Lean software development. Rigor and relevance analysis is performed to assess the quality of the resulted primary studies. Industrial survey was conducted in order to verify and extend the empirical evidence exists in Literature regarding metrics by finding which of them are more prominently being used. Moreover causes for dissatisfaction over outcome of metrics use for process improvements were observed by performing comparative analysis between unsatisfied respondents results and satisfied respondents results. Results: In total 20 metrics were identified from the studies having high rigor and high relevance. Moreover 11 out of these 20 metrics were identified to be prominently being used in industries using survey and other 9 metrics are found useful for Agile or Lean methods but need more awareness. Evidence from both SLR and survey shows that most of these identified or potential metrics are used for time associated purposes which are predictability, tracking, forecasting or planning, and very little evidence found for metrics that are being used directly for quality purpose. It was observed that some of the surveyed respondents who answered not satisfied with the metrics being used are not aware of the potential benefits these metrics can offer in Agile or Lean settings. Conclusion: Evidence from both SLR and survey shows that the identified 20 metrics are very important and useful for Agile or Lean methods. 11 out of these 20 metrics are prominently being used by industries and evidence shows for other 9 metrics are also useful for Agile but needs more awareness for industries to realize their potential benefits in large scale. Also, more evidence is found for metrics that are used for time related purposes which are being dominant and important in industries than quality focused metrics. Therefore, it is important for industries not only to know which metrics are appropriate for Agile or Lean but also to have a deep understating of metrics behaviors. This will help to realize the level predictability these metric’s offer in order to make right assumptions or planning. / Mobile no: (+46)-723110118

Context: The amount of software in solutions provided in various domains is continuously growing. These solutions are a mix of hardware and software solutions, often referred to as software-intensive systems. Companies seek to improve the software development process to avoid delays or cost overruns related to the software development.   Objective: The overall goal of this thesis is to improve the software development/building process to provide timely, high quality and cost efficient solutions. The objective is to select the origin of the components (in-house, outsource, components off-the-shelf (COTS) or open source software (OSS)) that facilitates the improvement. The system can be built of components from one origin or a combination of two or more (or even all) origins. Selecting a proper origin for a component is important to get the most out of a component and to optimize the development.  Method: It is necessary to investigate the component origins to make decisions to select among different origins. We conducted a case study to explore the existing challenges in software development.  The next step was to identify factors that influence the choice to select among different component origins through a systematic literature review using a snowballing (SB) strategy and a database (DB) search. Furthermore, a Bayesian synthesis process is proposed to integrate the evidence from literature into practice.   Results: The results of this thesis indicate that the context of software-intensive systems such as domain regulations hinder the software development improvement. In addition to in-house development, alternative component origins (outsourcing, COTS, and OSS) are being used for software development. Several factors such as time, cost and license implications influence the selection of component origins. Solutions have been proposed to support the decision-making. However, these solutions consider only a subset of factors identified in the literature.    Conclusions: Each component origin has some advantages and disadvantages. Depending on the scenario, one component origin is more suitable than the others. It is important to investigate the different scenarios and suitability of the component origins, which is recognized as future work of this thesis. In addition, the future work is aimed at providing models to support the decision-making process.