Browsing by study line "Ohjelmistot"

Context: The Bank of Finland, as the national monetary and central bank of Finland, possesses an extensive repository of data that fulfills both the statistical needs of international organizations and the federal requirements. Data scientists within the bank are increasingly interested in investing in machine learning (ML) capabilities to develop predictive models. MLOps offers a set of practices that ensure the reliable and efficient maintenance and deployment of ML models. Objective: In this thesis, we focus on addressing how to implement an ML pipeline within an existing environment. The case study is explorative in nature, with the primary objective of gaining deeper insight into MLOps tools and their practical implementation within the organization. Method: We apply the design science research methodology to divide design and development into six tasks: problem identification, objective definition, design and development, demonstration, evaluation, and communication. Results: We select the tools for the MLOps based on the user requirements and the existing environment, and then we design and develop a simplified end-to-end ML pipeline utilizing the chosen tools. Lastly, we conduct an evaluation to measure the alignment between the selected tools and the initial user requirements.

The rapid progress of communication technologies combined with the growing competition for talents and knowledge has made it necessary to reassess the potential of distributed development which has significantly changed the landscape of the IT industry introducing a variety of cooperation models and making notable changes to the software team work environment. Along with this, enterprises pay more attention to teams’ performance improvement, employing emerging management tools for building up efficient software teams, and trying to get the most out of understanding factors which significantly impact a team’s overall performance. The objective of the research is to systematize factors characterizing high-performing software teams; indicate the benefits of global software development (GSD) models positively influencing software teams’ development performance; and study how companies’ strategies can benefit from distributed development approaches in building high-performing software teams. The thesis is designed as a combination of a systematic literature review followed by qualitative research in the form of semi-structured interviews to validate the findings regarding classification of GSD models’ benefits and their influence on the development of high-performing software teams. At a literature review stage, the research (1) introduces a team performance factors’ model reflecting the aspects which impact the effectiveness of development teams; (2) suggests the classification of GSD models based on organizational, legal, and temporal characteristics, and (3) describes the benefits of GSD models which influence the performance of software development teams. Within the empirical part of the study, we refine the classification of GSD models’ benefits based on the qualitative analysis results of semi-structured interviews with practitioners from IT industry, form a comparison table of GSD benefits depending on the model in question, and introduce recommendations for company and team management regarding the application of GSD in building high-performing software teams. IT corporations, to achieve their strategic goals, can enrich their range of available tools for managing high-performing teams by considering the peculiarities of different GSD models. Company and team management should evaluate the advantages of the distributed operational models, and use the potential and benefits of available configurations to increase teams’ performance and build high-performing software teams.

Artificial Intelligence (AI) has revolutionized various domains of software development, promising solutions that can adapt and learn. However, the rise of AI systems has also been accompanied by ethical concerns, primarily related to the unintentional biases these systems can inherit during the development process. This thesis presents a thematic literature review aiming to identify and examine the existing methodologies and strategies for preventing bias in iterative AI software development. Methods employed for this review include a formal search strategy using defined inclusion and exclusion criteria, and a systematic process for article sourcing, quality assessment, and data collection. 29 articles were analyzed, resulting in the identification of eight major themes concerning AI bias mitigation within iterative software development, ranging from bias in data and algorithmic processes to fairness and equity in algorithmic design. Findings indicate that while various approaches for bias mitigation exist, gaps remain. These include the need for adapting strategies to agile or iterative frameworks, resolving the trade-off between effectiveness and fairness, understanding the complexities of bias for tailored solutions, and assessing the real-world applicability of these techniques. This synthesis of key trends and insights highlights these specific areas requiring further research.

A case study that studied the performance impact of a node.js component when it was refactored from monolith environment into independent service. The performance study studied the response time of the blocking part of JavaScript code in the component. The non blocking part of the code and the added network overhead from the refactoring were excluded from the performance review. Literature review didn’t show any related research that studied the performance impact of a node.js component when it was refactored from monolith into microservices. Many found studies were found that studied the response time and throughput of REST API build with node.js with comparisons to other programming languages. A study were found that related to refactoring an application from monolith into microservices. None of the found studies were directly related to the studied case. It was noted that the response time of the component improved by 46.5% when it was refactored from monolith into microservice. It is possible that when a node.js monolith application grows it starts to affect the throughput of the event loop affecting performance critical components. For the case component it was beneficial to refactor it into independent service in order to gain the 92.6ms in the mean response time.

This Master’s Thesis describes an original user study that took place at the University of Helsinki. The study compares and evaluates the usability of three different methods that are used in meeting rooms to share a private device’s screen on a big public screen in order to give a slideshow presentation: HDMI, VIA, and Ubicast. There were 18 participants. The study was conducted in a controlled environment, replicating a typical meeting room setup. The experiment consisted of screen mirroring tasks and an interview. In a screen mirroring task, the participants were asked to share their screen using each of the three technologies. They were provided with the necessary equipment and user guides if needed. Then the participants were given training on how to use the technologies, and they performed the tasks again. During the task, the time taken to complete each screen mirroring session was recorded, and any errors or difficulties encountered were noted. After completing the screen mirroring tasks, participants were interviewed to gather qualitative data on their experiences and preferences. They were asked about the ease of use, efficiency, and any difficulties they faced while using each technology. This information was used to gain insights into user preferences and potential areas for improvement in the respective technologies. To analyze the data, the System Usability Scale (SUS) scores and time taken to complete the screen mirroring tasks were calculated for each technology. Statistical analyses were conducted to determine any significant differences in SUS scores and time across the three technologies. Additionally, the interview data was analyzed using thematic analysis to identify common themes and patterns in the experiences of the users. HDMI emerged on the top, with Ubicast not far behind.

Software testing is an important part of ensuring software quality. Studies have shown that having more tests results in a lower count of defects. Code coverage is a tool used in software testing to find parts of the software that require further testing and to learn which parts have been tested. Code coverage is generated automatically by the test suites during test execution. Many types of code coverage metrics exist, the most common being line coverage, statement coverage, function coverage, and branch coverage metrics. These four common metrics are usually enough, but there are many specific coverage types for specific purposes, such as condition coverage which tells how many boolean conditions have been evaluated as true and false. Each different metric gives hints on how the codebase is tested. A common consensus amongst practitioners is that code coverage does not correlate much with software quality. The correlation of software quality with code coverage is a historically broadly researched topic, which has importance both in academia and professional practice. This thesis investigates if code coverage correlates with software quality by performing a literature review. Surprising results are derived from the literature review, as most studies included in this thesis point towards code coverage correlating with software quality. This positive correlation comes from 22 studies conducted between 1995-2021, which include Academic and Industrial studies, with studies put into multiple categories, such as Correlation or No correlation based on the key finding, and categories such as Survey studies, Case studies, Open-source studies, based on the study type. Each category has most studies pointing towards a correlation. This finding is in contradiction with the opinions of professional practitioners.

This master's thesis describes the development and validation of a uniform control interface for drawing robots with ROS2. The robot control software was tasked with taking SVG images as input and producing them as drawings with three different robots. These robots are the Evil Mad Scientist AxiDraw V3/A3, UFACTORY xArm Lite6, and virtual xArm Lite6. The intended use case for the robots and companion control software is experiments studying human perception of the creativity of the drawing robots. The control software was implemented over the course of a little over six months and used a combination of C++ and Python. The design of the software utilizes ROS2 abstractions such as nodes and topics to combine different components of the software. The control software is validated against the given requirements and found to fulfil the main objectives of the project. The most important of these are that the robots successfully draw SVG images, that they do so in a similar time frame, and that these images look very similar. Drawing similarity was tested by scanning images, aligning them using using minimal error, and then comparing them visually after overlaying the images. Comparing aligned images was useful in detecting subtle differences in the drawing similarity of the robots and was used to discover issues with the robot control software. MSE and SSIM were also calculated for a set of these aligned images, allowing for the effect of future changes made to the robot control software to be quantitatively evaluated. Drawing time for the robots was evaluated by measuring the time taken for drawing a set of images. This testing showed that the Axidraw's velocity and acceleration needed to be reduced by 56% so that the xArm Lite6 could draw in similar time.

The importance of software architecture design decisions has been known for almost 20 years. Knowledge vaporisation is a problem in many projects, especially in the current fast-paced culture, where developers often switch from project to another. Documenting software architecture design decisions helps developers understand the software better and make informed decisions in the future. However, documenting architecture design decisions is highly undervalued. It does not create any revenue in itself, and it is often the disliked and therefore neglected part of the job. This literature review explores what methods, tools and practices are being suggested in the scientific literature, as well as, what practitioners are recommending within the grey literature. What makes these methods good or bad is also investigated. The review covers the past five years and 36 analysed papers. The evidence gathered shows that most of the scientific literature concentrates on developing tools to aid the documentation process. Twelve out of nineteen grey literature papers concentrate on Architecture Decision Records (ADR). ADRs are small template files, which as a collection describe the architecture of the entire system. The ADRs appear to be what practitioners have become used to using over the past decade, as they were first introduced in 2011. What is seen as beneficial in a method or tool is low-cost and low-effort, while producing concise, good quality content. What is seen as a drawback is high-cost, high-effort and producing too much or badly organised content. The suitability of a method or tool depends on the project itself and its requirements.

Ohjelmistotuotannon ammattilaiset tarvitsevat monenlaisia kompetensseja. Yksi näistä kompetensseista on kyky elinikäiseen oppimiseen, joka on tarpeellinen laajalla ja jatkuvasti muutoksessa olevalla alalla. ICT-aloille muodostuneen osaajatarpeen myötä elinikäisen oppimisen rooli onkin alkanut korostumaan entisestään. Tutkielman tarkoituksena on ollut lisätä ymmärrystä elinikäisen oppimisen roolista ohjelmistotuotannon ammattilaisen näkökulmasta. Tutkielmassa on pyritty tunnistamaan, mitä oppimisen muotoja hyödynnetään sekä millaisiin tarkoituksiin niitä käytetään, mitkä elinikäisen oppimisen kompetenssin osatekijät ovat tärkeitä sekä mitä haasteita elinikäiseen oppimiseen liittyy. Tutkimuksen aineisto on kerätty puolistrukturoiduilla haastatteluilla ohjelmistotuotannon ammattilaisten kanssa. Näiden haastattelujen tuloksia on verrattu tutkielmaa varten suoritetun kirjallisuuskatsauksen tuloksiin. Oppimisen muodoista informaalia oppimista hyödynnetään eniten ja erityisesti pienempiin oppimistarpeisiin. Nonformaalia ja formaalia oppimista taas hyödynnetään isompiin tarpeisiin, mutta harvemmin. Motivaatio, tiedonhaku ja metaoppiminen korostuvat keskeisinä elinikäisen oppimisen kompetenssin osatekijöinä. Ajanpuute ja itsensä motivoiminen mielletään yleisimmiksi haasteiksi elinikäistä oppimista koskien. Myös tiedonlähteisiin liittyvät puutteet sekä puutteellinen ymmärrys metaoppimisesta mielletään vaikeuttavan elinikäistä oppimista. Tutkielman havainnot tukevat elinikäisen oppimisen kompetenssin keskeistä roolia ohjelmistotuotannon ammattilaisilla. Kehitettävää löytyy kuitenkin vielä ohjelmistotuotannon ammattilaisten valmiuksista elinikäiseen oppimiseen, esimerkiksi metaoppimista koskien. Havainnot perustuvat kuitenkin lyhyemmän aikaa ohjelmistotuotannon ammattilaisina työskennelleiden kokemuksiin, joten lisää tutkimusta tarvitaan etenkin pitempään työskennelleiltä ohjelmistotuotannon ammattilaisilta.

Etuuspohjaisen eläkejärjestelyn laskennan tavoitteena on selvittää eläkevakuutuksen ottajan säästö- ja eläkesuunnitelmien yhteensopivuus ottaen samalla huomioon sopimukseen kuuluvat turvat ja muut kulut. Vapaaehtoisiin eläkesopimuksiin tehtyjen lakimuutosten seurauksena tällainen laskenta on monimutkaistunut huomattavasti 2000-luvun aikana ja vanhoille järjestelmille luodut laskentamallit eivät aina suoriudu toivotulla nopeudella. Tämän tutkielman aiheena on Profit Software Oy:n Profit Life & Pension -vakuutustenhallintajärjestelmän optimointi edellä kuvatun laskennan osalta.