Build automation | EPFL Graph Search

Build automation is the process of automating the creation of a software build and the associated processes including: compiling computer source code into binary code, packaging binary code, and running automated tests. Historically, build automation was accomplished through s. Today, there are two general categories of tools: Build-automation utility This includes utilities like Make, Rake, CMake, MSBuild, Ant, Maven or Gradle (Java) etc. Their primary purpose is to generate build artifacts through activities like compiling and linking source code. Build-automation servers These are general web based tools that execute build-automation utilities on a scheduled or triggered basis; a continuous integration server is a type of build-automation server. Depending on the level of automation the following classification is possible: Makefile - level Make-based tools Non-Make-based tools Build script (or Makefile) generation tools Continuous-integration tools Configuration-management tools Meta-build tools or package managers Other A software list for each can be found in list of build automation software. Build-automation utilities allow the automation of simple, repeatable tasks. When using the tool, it will calculate how to reach the goal by executing tasks in the correct, specific order and running each task. The two ways build tools differ are task-oriented vs. product-oriented. Task-oriented tools describe the dependency of networks in terms of a specific set task and product-oriented tools describe things in terms of the products they generate. Although build servers existed long before continuous-integration servers, they are generally synonymous with continuous-integration servers, however a build server may also be incorporated into an ARA tool or ALM tool. Server types On-demand automation such as a user running a script at the command line Scheduled automation such as a continuous integration server running a nightly build Triggered automation such as a continuous integration server running a build on every commit to a version-control system.

Technology Strategy in Dynamic Environments: A Computational Analysis of the Automation of Routines, the Organization of AI, and the Evaluation of Technology Risk

Maximilian Wieland Hofer

In this dissertation, I develop theory and evidence to argue that new technologies are central to how firms organize to create and capture value. I use computational methods such as reinforcement learning and probabilistic topic modeling to investigate three topics: the automation of routines, the organization of artificial intelligence (AI), and the evaluation of technology risk. Overall, I argue that new technologies are not a panacea for the firm but require deliberate strategic planning to manage the potential downsides of myopic automation, AI interdependencies, and the disclosure of technology risks.In the first essay, I argue that while automation can increase productivity by reducing the costs of coordinating individuals, the automation of routines can also incur an indirect opportunity cost due to slow adaptation to environmental change. I develop a reinforcement learning simulation to model the impact of automation on the returns from the division of labor in dynamic environments and to show how automation incurs opportunity costs through lost learning and slow adaptation. Moreover, automation can be suboptimal when it brings about myopic behavior, i.e. high returns from the division of labor in the short term, but negative returns in the long term. Given the simulation results, I argue that firms need dynamic routines to simultaneously balance learning and automation. I open-source the simulation platform as OrgSim-RL on GitHub.In the second essay, I argue that a data-driven culture - what I define as a Data Clan - can help to coordinate complex interdependencies between AI components within a firm. I analyze in-depth semi-structured interview data with a hierarchical stochastic block model (hSBM) and hand-coding to find that managers focus primarily on building a strong culture and establishing high-quality data assets when allocating resources to AI initiatives. Given the results, I inductively develop implications for theory and argue that the emergence of a Data Clan can be a governance mechanism to reduce coordination frictions and build a competitive advantage in the age of AI.In the third essay, I argue that investors require a higher initial return to take on more technology risk disclosure during an IPO. I quantify the magnitude of disclosed risk and the risk disclosure topics based on a latent Dirichlet allocation (LDA) topic model of IPO prospectus text and find a return-for-risk association between text-based technology risk disclosure and underpricing. The study also finds evidence that owning granted patents is associated with a lower return-for-risk association, suggesting that intellectual property allows the disclosure of risk without losing the competitive advantage. I open-source the code for quantifying risk disclosure as RiskyData-LDA on GitHub.In summary, this dissertation develops theory and finds evidence across three essays to argue that leveraging new technologies requires deliberate strategic planning to manage potential downsides of new technologies, such as the opportunity costs of automation, coordination costs, and costs associated with raising capital. The results suggest three mitigating solutions: dynamic routines to balance learning and automation, a Data Clan to improve coordination, and disclosure through patents to reduce underpricing.

EPFL2022

Processus métier et composants logiciels pour la gestion intégrée des eaux en milieu urbain

Vincent Mottier

Water management in urban areas is a complex task because of the several interactions that exist between the different facets of the urban water system (surface and subsurface water, sewer system, water supply system, water and wastewater treatment plant, etc) and the many stakeholders in this context. It is necessary to reconsider current practices in order to shift from a sectored approach towards an integrated and global one. Such an approach implies that for each decision that has to be taken or each operation that has to be planned, numerous parameters must be considered and huge amounts of data have to be handled. Software tools offer in this context very interesting potentialities because of their ability to store, manage and exploit large volumes of spatial, thematic and temporal data. However, it turns out that such tools are not so easy to put into practice : exchange of information remains difficult, a lack of functions specific to water management has been stated, and the complexity of the domain itself makes the construction of dedicated software systems difficult and costly. The objectives of the present study are thus to develop concepts and a methodology allowing the development of software systems that support the management of urban water in an integrated and sustainable way. First, an identification of the criterions that must be fulfilled by such systems is carried out. It is shown that they must be: 1°) able to evolve in the same direction as water management practices; 2°) adaptable to the specific needs of their users; 3°) deployable on various computer systems configurations; 4°) able to interact with third party software systems; 5°) built and modified easily ; 6°) user friendly; and 7°) affordable. This research, taking into account these requirements, proposes to build software systems by assembling business components. Business components are reusable autonomous groups of software components that allow the handling of business objects, which are themselves high granularity objects that represent things active in the business domain. Indeed, such components allow the construction of software systems that exactly match users' requirements while taking advantage of the integration of preexisting parts : rapid development processes, cost reduction and increased quality. From a theoretical point of view, the proposal is built on three main principles : the complexity inherent to the domain of urban water management is tackled by segmentation. Each business component allows the handling of a coherent, limited and clearly defined set of concepts. A software tool can be built by integrating such business components and then be customized, thus recreating the complexity of the domain, but in a controlled manner; "real world" entities act as points of articulation between the businesses of the stakeholders : in the field of urban water management, the different actors handle, in the context of their business processes, abstractions of the same "real world" entities. Specific business components support the handling of these abstractions, submitting them to each user in a form that fits their needs. In this way, a business component, implementing a well defined set of concepts, will be used by the group of users concerned by these concepts, allowing an integrated approach of the different business processes; business components must be conceived in order to maximise their reusability potential in different software applications. Indeed, if this potential is high it is more worthwhile to develop the concerned business component. From a technical perspective, the proposal is based on : object orientation, which allows a direct mapping from the real world to the software system, and facilitates the development of systems that are modular, evolutive and easy to understand; software components, which allow the grouping of logically correlated functions and concepts into autonomous units. Such components are, with regards to their reusability, of an adequate level of granularity ; interoperability among components realised through a clear distinction between interfaces (the definition of the services offered) and implementations (the way of carrying out these services), associated with a standardisation of these interfaces. This research presents a way to identify, characterize and develop a set of business components specifically for urban water management software systems. The structure of such components is described. Two main kinds of business components are distinguished : entity components, which allow the handling of real world entities; and process components, which are designated to support specific business processes, and offer for this aim the adequate functions. Designated to be reused, business components must be constructed very meticulously, and the use of a software development method is for this purpose unavoidable. A method, dedicated for the development of business components in the domain of urban water management, is presented, whose characteristics are : 1°) to be based on the analysis of the business processes of the stakeholders; 2°) to allow rapid, iterative cycles, each of them leading to a set of operational business components; 3°) to allow the stepwise definition of a global reference mode1 of the urban water management domain that supports the development of coherent and non redundant business components; and 4°) to offer a technique that maximises the reusability potential of these components. The presented concepts, as well as the development method, are validated through prototyping. It is shown that a business component based approach of software systems offers a real opportunity to improve the business processes in the field of urban water management. Such components also offer possibilities to easily implement software systems that will help the monitoring and management of the urban water system. The enhancement of the value of the available data and the information exchange between stakeholders is facilitated. Thus, the development and use of business component based approaches must be encouraged. For this reason, this research concludes with the proposal of an organisational process aimed to stimulate and coordinate the setting up of a "business component market" for urban water management systems.

EPFL2001