The Big Enterprises all over the world are setting up their services in cloud as this is cheaper and offers a lot of other benefits. These services have to be updated from time to time and for this, the enterprises have to upgrade their systems in the cloud. During these upgrades, the enterprises face a lot of problems known as compatibility issues. The companies are investing big time to avoid these compatibility issues. The investment could be in money, time, labor etc. also known as effort. Therefore, it is in our interest to attempt to reduce this effort. In this study, our main objectives are to calculate the effort required to maintain the backward compatibility during the upgrade process in the cloud and to find ways to reduce this effort. Reducing the effort will help the companies cut down their investment. A hypothesis was introduced saying that the network usage was dependent on the upgrade method chosen. We have chosen experimentation to be the suitable research method. To run our experiments, we have created a virtual environment similar to that of Ericsson. The experimental values were recorded. We recorded the values such as code complexity, total time for the upgrade process and the network usage during the experiment. Using these values, we tried to estimate the effort and scale it to real time scenarios. Using ANOVA we proved that our null hypothesis was correct. The results have then been discussed in detail and RQ1 is answered. Later RQ2 is answered based on the answer for RQ1. Through our analysis we were able to get a rough estimate of the effort (labor, time, cost) required to maintain backward compatibility. We propose that the existence of the tool mentioned will reduce the effort considerably. The features of the tool are explained in detail. Some future work as the actual development of the tool has been suggested.

abstract: Dynamic software update (DSU) enables a program to update while it is running. DSU aims to minimize the loss due to program downtime for updates. Usually DSU is done in three steps: suspending the execution of an old program, mapping the execution state from the old program to a new one, and resuming execution of the new program with the mapped state. The semantic correctness of DSU depends largely on the state mapping which is mostly composed by developers manually nowadays. However, the manual construction of a state mapping does not necessarily ensure sound and dependable state mapping. This dissertation presents a methodology to assist developers by automating the construction of a partial state mapping with a guarantee of correctness. This dissertation includes a detailed study of DSU correctness and automatic state mapping for server programs with an established user base. At first, the dissertation presents the formal treatment of DSU correctness and the state mapping problem. Then the dissertation presents an argument that for programs with an established user base, dynamic updates must be backward compatible. The dissertation next presents a general definition of backward compatibility that specifies the allowed changes in program interaction between an old version and a new version and identified patterns of code evolution that results in backward compatible behavior. Thereafter the dissertation presents formal definitions of these patterns together with proof that any changes to programs in these patterns will result in backward compatible update. To show the applicability of the results, the dissertation presents SitBack, a program analysis tool that has an old version program and a new one as input and computes a partial state mapping under the assumption that the new version is backward compatible with the old version. SitBack does not handle all kinds of changes and it reports to the user in incomplete part of a state mapping. The dissertation presents a detailed evaluation of SitBack which shows that the methodology of automatic state mapping is promising in deal with real world program updates. For example, SitBack produces state mappings for 17-75% of the changed functions. Furthermore, SitBack generates automatic state mapping that leads to successful DSU. In conclusion, the study presented in this dissertation does assist developers in developing state mappings for DSU by automating the construction of state mappings with a correctness guarantee, which helps the adoption of DSU ultimately. / Dissertation/Thesis / Doctoral Dissertation Computer Science 2015

Dual task studies have found that Task 2 response information is activated during Task 1 response selection, and can have a priming effect on Task 1. This is called the backward compatibility effect (BCE). Giammarco et al. (2016) found that single-task practice of Task 2 in the context of a random, filler task (Practice-T2 condition) extinguished BCE development in a subsequent dual-task. On the other hand, practicing Task 2 in the context of Task 1 (Practice-Both condition) promoted BCE development in subsequent dual-tasks. Experiment 1a sought to replicate this context-specific disruption of BCE development by presenting participants with a single-task practice phase where they practiced Task 2 along with a filler task, and then observed BCE development in a subsequent dual-task phase. Experiment 1b addressed a counterbalancing issue in Experiment 1a. Experiment 2 was an exact replication of the Practice-T2 condition used in Giammarco et al. (2016). Overall, we conceptually replicated the context-specific disruption of BCE in Experiment 2, but not in Experiments 1a and 1b. Further study is warranted to determine the effect of specific response features on the learning context of Task 2. / Thesis / Master of Science (MSc) / Backward compatibility effects (BCEs) have been consistently observed in dual task paradigms. BCEs occur when Task 1 and Task 2 response information are congruent: participants respond faster to Task 1 when the two tasks require congruent responses than when they require incongruent ones. This suggests that there is some parallel processing of Task 2 while performing Task 1. The purpose of this study was to explore the episodic account of BCE development. Since episodic memories are context-specific, BCEs should also be context-specific, according to the episodic account. By manipulating the context of Task 2 learning, we tested whether this affected subsequent BCE development. Our findings suggest that context-specific disruption of BCE development is possible, but depends on other factors as well.

Tato diplomová práce se zabývá API a ABI kompatibilitou Java knihoven. Jsou popsány typy kompatibility a analyzovány změny API, které vedou k zdrojové či binárni nekompatibilitě. Dále je provedena analýza existujících nástrojů, které provádějí zjišťování nekompatibility. Vhodný nástroj z předchozí analýzy je vybrán a rozšířen. Na základě rozšířeného nástroje je vytvořena serverová aplikace, která poskytuje informace o kompatibilitě sledovaných knihoven.