An empirical study of imputation techniques for software data sets

Software Project Effort/Cost/Time Estimation has been one of the hot topics of research in the current software engineering industry. Solutions for effort/cost/time estimation are in great demand. Knowledge of accurate effort/cost/time estimates early in the software project life cycle enables project managers manage and exploit resources efficiently. The constraints of cost and time can also be met. To this day, most companies rely on their historical database of past project data sets to predict estimates for future projects. Like other data sets, software project data sets also suffer from numerous problems. The most important problem is they contain missing/incomplete data. Significant amounts of missing or incomplete data are frequently found in data sets utilized to build effort/cost/time prediction models in the current software industry. The reasons are numerous and the missingness is inevitable. The traditional approaches used by the companies ignore all the missing data and provide estimates based on the remaining complete information. Thus, the very estimates are prone to bias. In this thesis, we investigate the application of a few well-known data imputation techniques (Listwise Deletion, Mean Imputation, 10 variants of Hot-Deck Imputation and Full Information Maximum Likelihood Approach) to six real-time software project data sets. Using the imputed data sets we build effort prediction models to evaluate their performance. We study the inherent characteristics of software project data sets such as data set size, missing mechanism, pattern of missingness etc and provide a generic classification schema for all software project data sets based on their characteristics. We further implement a hybrid methodology for solving the same. We perform useful experimental analyses and compare the impacts of these methods for enhancing prediction accuracies. We also highlight the conditions to be considered and measures to be taken while using an imputation technique. We note the ideal and worst conditions for each method. Finally, we discuss the findings and the appropriateness of each method for data imputation to software project data sets

Laadunvalvontametodologian ja –järjestelmän käyttö teollisessa sovelluskehityksessä – Soveltuvuustutkimus

Ensuring software quality is important for achieving a competitive advantage in the market. Also, it is essential in critical systems, where a computer program cannot fail under any circumstances. In software projects, the best way to accomplish quality is to continuously monitor the state of the product and the development process. This means, that measurements on the software have to be done. However, as it is not adequate to measure everything, the relevant quality characteristics have to be defined. This is very context-specific and should thus be done for each project separately. In this thesis, the deployment of quality monitoring in software development projects was studied. This included defining a quality model and designing, deploying and using a quality monitoring program. These activities were facilitated by the U-QASAR methodology and platform that provide guidance and support for quality monitoring by measurement data integration. The study consisted of two parts: a multiple case study and constructive research. The case study was conducted to explore the case project members’ experiences on quality monitoring. Observations, interviews and questionnaires were used as research instruments. A constructive research method was used to evaluate the data integration in the U-QASAR platform. Data integration adapters were explored and developers were interviewed and finally a new adapter was implemented. In both parts, thematic analysis was used to process the data. The case study results showed that quality monitoring can be deployed even in small-scale software projects, but there are certain challenges. For example, it is difficult to connect objective software measurements to more abstract quality objectives. Moreover, practitioners’ knowledge on the terminology of software measurement and software quality is not something that can be assumed. However, it is important that the semantic structure is taken care of in order to achieve common understanding. The constructive research revealed needs for further development regarding the data integration architecture of the U-QASAR platform.Ohjelmistokehityksessä laadunvarmistus on tärkeää, sillä sen avulla voidaan saavuttaa parempi markkina-asema. Ohjelmiston laatu on tärkeää myös kriittisissä systeemeissä, joiden vikaantuminen voi johtaa esimerkiksi mittaviin taloudellisiin menetyksiin. Ohjelmistokehitysprojekteissa laadukas tuote voidaan parhaiten saavuttaa jatkuvasti tarkkailemalla projektin tilaa, mikä edellyttää mittauksia. Kaikkea ei kuitenkaan ole kustannustehokasta mitata, joten on tärkeää määrittää kyseiselle tuotteelle ja projektille tärkeät laatuominaisuudet. Tässä työssä tutkittiin laadunvalvonnan käyttöönottoa ohjelmistokehitysprojekteissa. Siihen liittyviä aktiviteetteja olivat laatumallin määrittely sekä laadunvalvontaohjelman suunnittelu, käyttöönotto ja käyttö. Toiminnot toteutettiin käyttäen U-QASAR-metodologiaa ja -alustaa, jotka tarjoavat ohjausta ja tukea mittausdataintegraatiolla toteutettavaan laaduntarkkailuun. Tutkimus koostui kahdesta osiosta: monitapaustutkimuksesta ja konstruktiivisesta tutkimuksesta. Tapaustutkimus tehtiin, jotta laadunvalvonnasta saatavia kokemuksia voitaisiin tutkia. Tutkimusinstrumentteina käytettiin havainnointia, haastatteluja sekä kyselyitä. Konstruktiivisessa tutkimuksessa kohteena oli U-QASAR-alustan dataintegraation toteutus. Jo kehitettyjen integraatioadaptereiden rakennetta tutkittiin ja kehittäjiä haastateltiin. Lopuksi uusi adapteri kehitettiin. Molemmissa tutkimusosioissa temaattista analyysiä käytettiin datan käsittelyyn. Työn tulokset osoittivat, että laadunvalvontaa voidaan tehdä pienissäkin ohjelmistoprojekteissa, mutta tietyt haasteet on otettava huomioon. Esimerkiksi objektiivisten mittausten yhdistäminen abstraktimpiin laatuominaisuuksiin todettiin vaikeaksi. Lisäksi havaittiin, että laatuterminologian ei voida olettaa olevan hallussa kaikilla projektin sidosryhmillä. On kuitenkin tärkeää, että semanttinen konsensus säilytetään yhteisen ymmärryksen takaamiseksi. Konstruktiivisen tutkimuksen tulokset osoittivat, että U-QASAR-alustan dataintegraatioarkkitehtuuri vaatii jatkokehitystä

An Evaluation of Software Measurement Processes in Pakistani Software Industry

Implementing a successful measurement process is a challenging task. Most measurement studies report measurement models, experiences, and lessons learned based on pilot projects or case studies in a limited scope to overcome specific challenges. This paper identifies 14 basic measurement practices and proposes a model of 18 success factors for implementing measurement processes with respect to the identified measurement theories in our systematic literature review (SLR), i.e., A systematic literature review on software measurement programs, by Tahir et al. , 2016. In addition, a survey is conducted to evaluate the state of measurement practices and to validate the proposed model based on the feedback from 200 software professionals working in Pakistani software industry. The state of measurement practices in the industry is mostly not according to the identified measurement theories in the SLR. For instance, more than 50 measurement models reported in the literature but only 10% software organizations follow any measurement model. 75% of organizations do not follow any measurement standard. 80% software organizations do not use any measurement tool. The proposed model is validated by applying structural equation modeling on the survey data. Furthermore, among 18 success factors, it is statistically significant that Pakistani software professionals strongly believe in necessity of three factors for successful implementation of a measurement process, i.e., synchronization between measurement process and software process improvement, use of measurement standards, and use of measurement models. In addition, they also believe that a successful measurement process will improve prediction, monitoring and management of software projects, and support in achievement of individual and organization-wide objectives. Software organizations might consider this paper in planning and improving their measurement processes

Modelo de calidad para el software orientado a objetos

El software ha obtenido en la actualidad una gran importancia en todos los ámbitos de la vida cotidiana. Es indudable que la calidad del software juega un papel fundamental en todo desarrollo informático, aunque en ocasiones no se le presta la suficiente atención, quizás debido a los relativamente escasos trabajos relacionados con este tema desarrollados hasta la fecha. En el presente trabajo, se plantea la necesidad de un modelo de calidad completo. Para cubrir esta necesidad se presenta un nuevo modelo de calidad, obtenido tras un estudio pormenorizado de los modelos de calidad existentes, centrado en el paradigma orientado a objetos. Este modelo de calidad muestra cómo la calidad del software se descompone en una serie de factores y éstos, a su vez, se descomponen en un conjunto de criterios medibles utilizando medidas. El modelo incluye un amplio conjunto de medidas, diseñadas especialmente para su aplicación dentro del paradigma orientado a objetos. Para completar el modelo, se ha diseñado un sencillo método de aplicación de este modelo de calidad para que pueda ser utilizado de una forma simple por los desarrolladores de sistemas informáticos orientados a objetos. El modelo de calidad definido se ha validado realizando un juego de experimentos. Estos experimentos han consistido en la aplicación del modelo sobre una serie de desarrollos orientados a objetos. Los resultados obtenidos han demostrado su utilidad práctica para determinar tanto la calidad global de los sistemas, como para identificar aquellas partes del sistema susceptibles de ser mejoradas. Con este trabajo, se llena un importante hueco existente en esta área, pues, en primer lugar, no existen modelos de calidad completos para la orientación a objetos. En segundo lugar, aunque hay medidas para la orientación a objetos, no se han asociado a los atributos que determinan la calidad del software, por lo que su utilidad, tal cual fueron definidas, resulta bastante cuestionable. Para finalizar, nunca se ha asociado un modelo de calidad con una método de aplicación, por lo que su utilidad quedaba considerablemente mermada, quedando a expensas de la habilidad y experiencia del Ingeniero del Software que lo utilizara