Conference PaperPDF Available

Impact of Overtime and Stress on Software Quality

  • January 2008
DOI:10.13140/RG.2.2.12815.59041
  • Conference: The 4th International Symposium on Management, Engineering, and Informatics: MEI 2008
  • At: Orlando, FL
Authors:
Balaji Akula at CT Group of Institutions
Balaji Akula
James Cusick at IEEE Computer Society
James Cusick
  • IEEE Computer Society
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Abstract

Producing software requires an environment conducive to concentration and measured work. In this paper several projects are presented with varying degrees of overtime where the resultant quality of the applications in terms of defect counts varies directly. It is proposed that stress in the work environment driven by overtime adversely affects software quality.
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1
Impact of Overtime and Stress on
Software Quality
Balaji Akula & James Cusick
Wolters Kluwer Corporate Legal Services
New York, NY
{balaji.akula, james.cusick}@wolterskluwer.com
ABSTRACT
Producing software requires an environment conducive to concentration
and measured work. In this paper several projects are presented with
varying degrees of overtime where the resultant quality of the applications
in terms of defect counts varies directly. It is proposed that stress in the
work environment driven by overtime adversely affects software quality.
Introduction
Stress can be defined as any type of change that causes physical, emotional or
psychological strain. (Scott, E., 2007). From time to time stress overwhelms us, in many
cases this is indeed normal (hr.blr.com, Oct 2006). While it is virtually impossible for
most people to eliminate stress we can certainly take steps to avoid stress and its potential
to cause debilitating side effects where possible. According to Peggy Duncan (Scott,
2007), stress is caused due to a number of factors: disorganization, unclear goals, too
many personal phone calls, disjointed processes, no routines, poor planning,
procrastination, lack of focus, and lack of training are some of the reasons for stress.
Statistical data from the National Institute for Occupational Health and Safety has
disclosed that the number of American workers who consider stress to be a major
problem in their lives has more than doubled during the past ten years
(Missoncontrol.com, Sep 9 2007). Among professions, software engineering can produce
stressful environments for its participants. In this paper the relationship of stressors to
software quality is explored.
2
Background
As a starting point the question was asked, what is the one thing that can cause a high
number of defects and do so repeatedly? There is no single answer to this question. Some
of the reasons include but are not restricted to the lack of proper requirements change
process, technical challenges, aggressive schedule, improper planning, stress, etc. This
paper focuses on the impact of stress on the quality of product developed by software
engineers over a period of 2 years. Any stress related health issues were not studied and
are not reported here. The background for this effort stemmed from a high number of
defects noticed during quality assurance of the software lifecycle.
We have made an attempt to establish a link between an aggressive schedule and its
negative impact on software quality. The general pattern of this linkage is given below:
Aggressive Schedule Overtime Stress Defects
As per the above pattern, Defects will increase when a team is working on an aggressive
schedule. Putting teams under pressure leads to increases in overtime thus reducing
concentration on quality and more focus on output. In general mental activity and clarity
is required for any mind (Jeffries, E.R 2007). The more overtime the worker spends
means that his mental activity and clarity decreases while stress increases. As
corroborated by data presented in this paper it is proposed that defects are injected as a
result of stress caused due to overtime. Moreover as per recent studies a tired/stressed
programmer has double the chances of putting in a very serious bug but has probably also
put in a much higher percentage of smaller ones (Jeffries, E.R 2007).
Defects are a very important metric in software engineering. When defects are taken out
of context it gives a bad impression of the product in question. However, when taken as a
whole, along with the project, the number of lines of code that is written, project
duration, etc., it may not prove to be the demon that it is usually made out to be. Poor
quality can act as a dampener in the following ways:
3
1) Can allow teams to deviate from core project activities
2) Can result in loss of trust between QA & Development teams
3) Increased stress during triage where defects are discussed, and in some cases
can have a personal effect detrimental to project.
4) Worst case may result in delay of the project.
5) Finger pointing over defects among teams kills the team spirit.
6) Teams end up spending more time fixing defects than developing business
critical features.
One of the most important reasons that stress is generated, according to our observations,
is due to aggressive schedules especially being repeated project after project. While many
project team members (the average age of the team member was 26 years) can absorb the
health related issues of stress; their productivity suffers and manifests in the form of
defects (read as poor quality). We have studied 4 projects over a period of 2 years and
have observed the defect levels for each of the projects. All projects had a few
similarities; all were web applications built using Microsoft .NET 2.0 technologies, 3 out
of the 4 projects had an aggressive schedule, and all were completed as planned, 3
projects had a high defect rate. The results are provided below.
Results
Data on four projects were analyzed. The amount of scheduled work hours, actual
overtime hours, and number of defects were recorded on each of these production
releases. The overtime hours were seen as a reliable indicator of stress on the project
team members and the level of defects was seen as an output of the stress on the project
team members. In the diagrams below the actual data is reported from these commercial
projects.
4
Effort, Overtime, and Defect Levels
0
100
200
300
400
500
600
700
800
900
Project 1Project 2Project 3Project 4
Project
Hours
0
500
1000
1500
2000
2500
Defects
Estimated
Overtime
Defects
Fig 1: Project wise Effort, Overtime and Defects levels
It is proposed that high stress levels results in less quality and that high stress levels can
been produced by high overtime. This observation is evident in Figure 1. As can be seen
from the graph (actual data is provided in Table 1), the defect levels are low when
overtime is lower or zero. Figure 1 plots the estimated hours for each project and the
actual overtime hours for each project. Additionally, the line plot indicates the level of
defects for each project. As can be seen, the projects with overtime had higher defect
rates.
OverTime Report
0
100
200
300
400
500
600
700
800
900
Project1 Project 2 Project 3 Project 4
Project Wise OT (hrs)
Estimated Time (hrs)
Estimated Hours
Avg. OT / Person
5
Fig2: Overtime hours spent on each project
The Graph in Figure 2 depicting the actual estimated time for construction and overtime
effect on the team to complete project on time and as planned. Please also refer to the
same in table format (Table 1). In most cases overtime runs at 10% of the estimated effort
hours. Specifically, overtime ran at 150 to 200 hours per person on these projects. These
projects are executed with a construction phase of usually 8 weeks plus an additional 8
weeks of QA. Thus, the projects are executed in a compressed time frame using overtime
work to balance for the aggressive scheduling.
Project PROJECT 1 PROJECT 2 PROJECT 3 PROJECT 4
Estimated
person hours 784 416 416 528
Overtime
person Hours 175 167 0 198
Defects 2038 1545 142 2000
Table1. Table data of Project wise defect count in relation to overtime.
Observations
From the above results, the following can be observed
¾ Defect counts increases when overtime is extensive.
¾ Stress on workers, and on Projects (via defects, delay etc) develops when projects
are not planned and executed properly (that is, with excessive use of overtime).
In general overtime may be requested under the following conditions:
¾ To accommodate Changes/Requirements not in original estimates.
¾ Natural/unprepared calamities like viral outbreak, snowstorm etc.
¾ Technical challenges that cause delays in implementation.
¾ Under estimation
If a project has clocked overtime not due to any of the above reasons then the primary
cause could well be due to incorrect planning. By incorrect planning it could mean
that the estimates were aggressive or planning itself was way off the mark. From the
6
above data in table 1, it appears that the latter was the case, as barring ARWR2 all
projects required overtime to complete as planned.
While it is comforting to note that the projects were completed on time, the stress
factor to developers/project team is largely ignored as the team moves on to the next
project or is consumed by other activities. Whatever the case the stress is continued
from one project to another, as history repeats itself time after time.
A correlation of 0.98 (between overtime data and defect count) clearly indicates the
effect of overtime driven stress on increased defect count. The defect count in
PROJECT 3 is only 7% when compared to the average defect counts of other
releases. The possible reason for PROJECT 3 having low defects and high quality can
be adduced to the following:
¾ Zero overtime hours spent during project.
¾ Correct Planning and Estimation
There are alternative ways to interpret this data. One way of viewing this data is that the
defects themselves lead to overtime which leads to stress. The question would be what
leads to the defects in the first place. A second alternate view is around the volume of
software being written. In this view since the more code that is written generates more
defects then the high level of production of code leads to more defects which leads to
overtime. These and other alternate views may have validity but they were not deeply
considered, instead the primary view of this paper remains that aggressive scheduling
drives defect levels which drives overtime.
Conclusion
More and more industries are looking at ways to reduce workplace stress; however the
big question is how to accomplish this effectively and efficiently. By neglecting or not
paying enough attention to workplace stress companies will end up nullifying their
investment. The evidence that links stress to poor quality has been shown above. Critics
7
will argue that other factors also play a role in the quality of software products. There is
no question about this premise. However, stress is one of the important factors that can
lead to bad quality products as we have shown. According to Michael Beck (2005)
productivity drops significantly when we are under stress and our ability to think clearly
is impacted. A survey conducted in October 2006 indicates a loss of 1 hour or more per
day in productivity due to stress (hr.blr.com, Oct 2006). As the saying goes it is better to
strike when the iron is hot. So act now.
Some of the important lessons that can be learned are
¾ Avoid stress to improve productivity.
¾ Plan and do not under-plan or be too aggressive.
¾ Estimation approach – we can revisit the estimation practice that is followed
and improve if required. We should try to follow what is in the estimate and
try not to cut down on the same for whatever reasons.
¾ Defect prediction – Using our experience gained from previous projects it
would make sense to predict the defect density based on estimation,
component inventory, and previous data so that we can adjust our estimates
accordingly.
¾ Quality development – we should strive to go for quality and avoid
development during QA phase of the lifecycle. As mentioned below the cost
of fixing defect is not only high but the probability of introducing new defects
is high too.
Both the above are easy to avoid in most scenarios. The exception being projects which
are designated as “Fast Track” and is aggressive from the beginning. The benefits are
huge. I would imagine that the following would benefit software teams in the short and
long term if implemented according to the nature of project:
1. Less stress to software engineer results in more productivity.
8
2. Less stress means low defects and indirectly less wrangling with the QA/
Project Management during triage. We are all aware of the battles between QA
and Software Engineering teams. We can channel all the energy to good use
instead of wrangling over defects.
3. Having a plan which has a buffer (say 2 weeks for example) is better than under-
planning. Experienced Software developers are aware that the requirements keep
changing, and/or new requirements keep cropping all the time. Hence having a
buffer of a few weeks helps the project and in no way would delay the same.
4. It's well-established that it takes less time and costs much less to prevent defects
than to fix them. A recent article in Crosstalk, the Journal of Defense Software
Engineering, reports that "finding and fixing bugs is the most expensive cost
element for large systems and takes more time than any other activity." (Jeffries,
E.R, 2007)
5. Last but not the least by planning with the human factor in mind we will be
appreciated for trying a humane approach to software development. There is
sufficient stress in globally outsourced development without driving overtime
hours skyward.
9
References
1. http://hr.blr.com/news.aspx?id=19241. October 13, 2006, Survey: Workplace Stress
Has Substantial Impact on Productivity.
2. Elizabeth, Scott - http://stress.about.com/od/managementtools/a/peggyinterview.htm,
09/20/2007, An Interview with Productivity Expert Peggy Duncan.
3. Jeffries, E Ronald - http://www.xprogramming.com/xpmag/jatSustainablePace.htm,
2007. Viewed on Oct 16 2007.
4. http://www.missioncontrol.com/p_mcsys_stress.htm, 09/20/2007, How does stress
Impact Productivity. – Last line, Para 1.
5. Beck, Michael - Manage Stress to Boost Productivity, 2005
http://www.xleaders.com/Articles/Beck/Manage%20Stress%20to%20Boost%20Prod
uctivity.pdf. Viewed on Oct 15 2007.
Further Reading
1. http://main.uab.edu/show.asp?durki=57296 - Ten Ways to Control Stress
2. http://www.webmd.com/anxiety-panic/guide/tips-to-control-stress - Mental Health:
Tips to Control Stress
3. http://www.drake.co.nz/dbr/pdf/work_place_stress.pdf. - When Workplace Stress
stifles productivity.
... It was observed by Nishikitani et al. [11] and Karita et al. [12] that overtime work and long shifts have a positive correlation with stress indexes such as depression, anger, hostility and increase in equilibrium and motor-related problems on IT professionals. Also regarding the effect on the software that developers produce, Akula and Cusick [13] found out that longer overtime work causes increased stress, which in turn translates to higher defect counts in software projects. The implication of these effects is bad quality software since developers continue to focus more on quick and rapid completion of tasks rather than quality. ...
... Akula and Cusick [13] carried out a statistical survey on four real-life software projects to analyze the impact of overtime on software quality. The number of scheduled work hours, actual overtime hours, and a number of defects were recorded on each of the projects. ...
... Results from experiments revealed that the approach is significantly better than standard NSGA-II in 76% of experiments and significantly outperformed standard overtime planning strategies used in the industry. However, their formulation failed to assess the negative effect of overtime on software quality even when empirical studies in the literature [11,13] have revealed that the effort required to correct additional errors introduced by developers working overtime outweighs the productivity gains. ...
MEMETIC APPROACH FOR MULTI-OBJECTIVE OVERTIME PLANNING IN SOFTWARE ENGINEERING PROJECTS
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  • Dec 2019
Software projects often suffer from unplanned overtime due to uncertainty and risk incurred due to changing requirement and attempt to meet up with time-to-market of the software product. This causes stress to developers and can result in poor quality. This paper presents a memetic algorithmic approach for solving the overtime-planning problem in software development projects. The problem is formulated as a three-objective optimization problem aimed at minimizing overtime hours, project makespan and cost. The formulation captures the dynamics of error generation and propagation due to overtime using simulation. Multi-Objective Shuffled Frog-Leaping Algorithm (MOSFLA) specifically designed for overtime planning is applied to solve the formulated problem. Empirical evaluation experiments on six real-life software project datasets were carried out using three widely used multi-objective quality indicators. Results showed that MOSFLA significantly outperformed the existing traditional overtime management strategies in software engineering projects in all quality indicators with 0.0118, 0.3893 and 0.0102 values for Contribution (IC), Hypervolume (IHV) and Generational Distance (IGD) respectively. The proposed approach also produced significantly better IHV and IGD results than the state of the art approach (NSGA-IIV) in 100% of the project instances. However, the approach could only outperform NSGA-IIV in approximately 67% of projects instances with respect to IC.
... Progress equals fast, and fast equals success, which is a recipe for addiction [Bro14]. In addition to the known effects of stress on software quality as evaluated by Akula and Cusick [AC08], Amin et al. [ABHR11] found that occupational stress also negatively affects knowledge sharing, which leads to long-term detrimental effects for software systems development, particularly in global development settings. ...
... Sleep deprivation and disrupted circadian rhythms may lead to adverse metabolic consequences [BCO + 12], all the way up to increasing the risk for developing cancer [HS13]. The effects of sleep deprivation are clearly negative, and stressed software engineers report a decreased quality of sleep [AC08], which in turn negatively impacts health [HST + 17]. This also leads to economic losses, recognized in the US, but also United Kingdom, Japan, Germany, and Canada [HST + 17], estimated to between $280 billion and $411 billion for the US in 2020, depending on the scenario, and between $88 billion and $138 billion for Japan. ...
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Context. Computer workers in general, and software developers specifically, are under a high amount of stress due to continuous deadlines and, often, over-commitment. Objective. This study investigates the effects of a neuroplasticity practice, a specific breathing practice, on the attention awareness, well-being, perceived productivity, and self-efficacy of computer workers. Method. We created a questionnaire mainly from existing, validated scales as entry and exit survey for data points for comparison before and after the intervention. The intervention was a 12-week program with a weekly live session that included a talk on a well-being topic and a facilitated group breathing session. During the intervention period, we solicited one daily journal note and one weekly well-being rating. We replicated the intervention in a similarly structured 8-week program. The data was analyzed using a Bayesian multi-level model for the quantitative part and thematic analysis for the qualitative part. Results. The intervention showed improvements in participants' experienced inner states despite an ongoing pandemic and intense outer circumstances for most. Over the course of the study, we found an improvement in the participants' ratings of how often they found themselves in good spirits as well as in a calm and relaxed state. We also aggregate a large number of deep inner reflections and growth processes that may not have surfaced for the participants without deliberate engagement in such a program. Conclusion. The data indicates usefulness and effectiveness of an intervention for computer workers in terms of increasing well-being and resilience. Everyone needs a way to deliberately relax, unplug, and recover. Breathing practice is a simple way to do so, and the results call for establishing a larger body of work to make this common practice.
... Many believe that crunch time within the games industry is part of the work culture and therefore it can not be changed, leading to employees just accepting it [1], [2]. Recent research claims that crunch time itself can contribute to late deliveries and low quality software, making it a vicious cycle [1], [3]. Sleep deprivation can significantly reduce developers ability to make rational design decisions and produce high quality software [1]. ...
... We believe this is due to the fact that overworked and burnt out employees have a tendency of making more mistakes and thus create more bugs and reduce the quality. This was also noted by Akula & Cusick [3] whose research shows that stress lead to poor quality software and that avoiding stress will lead to increased productivity. Mini Crunches however only had positive impacts on the product. ...
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... They also observed an increase in equilibrium-and motorrelated problems on Japanese workers from the IT sector subjected to long shifts [24]. Regarding the outcome of developers' work, Akula and Cusick [4] and DeMarco [10] relate overtime work with higher error generation rates in software projects. DeMarco and Lister [11] also relate excessive overtime with increased personal attrition, which may reduce knowledge exchange amongst developers [27] and hamper the ability of a company to hold expertise and properly deal with developer turnover [2]. ...
... However, it does not consider the negative impact of overtime on product quality. Previous studies [10] [4] have presented empirical evidence that the work required to fix extra errors produced by tired developers may subdue the productivity gains brought by working overtime. ...
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IT professionals are frequently subject to working overtime, even knowing that excessive overtime has negative effects both on their lives and the software they produce. This contrast creates the need for overtime policies that attend to the demands of a project using as few overtime hours as possible. However, our knowledge about the dynamics of overtime work and the effects of distinct policies on a software project is limited. In this paper we introduce a formulation for the overtime planning problem which extends the state-of-art by considering both the positive effects of overtime on productivity and its negative effects on product quality. We use heuristic search to explore close to optimal overtime allocations under this formulation and report lessons learned by analyzing these allocations. We present an empirical study that compares our approach with practices from the industry and a similar formulation without negative effects. Evidence supports the industrial practice of concentrating overtime in the second half of a project's schedule. Results also show that ignoring the flip-side of the productivity gains brought by overtime may lead to wrong decisions. For instance, excessive overtime may lead a manager to underestimate project cost and duration by 5.9% and 9.2%, respectively.
... Progress equals fast, and fast equals success, which is a recipe for addiction (Brown 2014). In addition to the known effects of stress on software quality as evaluated by Akula and Cusick (2008), Amin et al. (2011) found that occupational stress also negatively affects knowledge sharing, which leads to long-term detrimental effects for software systems development, particularly in global development settings. ...
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Context Computer workers in general, and software developers specifically, are under a high amount of stress due to continuous deadlines and, often, over-commitment. Objective This study investigates the effects of a neuroplasticity practice, a specific breathing practice, on the attention awareness, well-being, perceived productivity, and self-efficacy of computer workers. Method The intervention was a 12-week program with a weekly live session that included a talk on a well-being topic and a facilitated group breathing session. During the intervention period, we solicited one daily journal note and one weekly well-being rating. We created a questionnaire mainly from existing, validated scales as entry and exit survey for data points for comparison before and after the intervention. We replicated the intervention in a similarly structured 8-week program. The data was analyzed using Bayesian multi-level models for the quantitative part and thematic analysis for the qualitative part. Results The intervention showed improvements in participants’ experienced inner states despite an ongoing pandemic and intense outer circumstances for most. Over the course of the study, we found an improvement in the participants’ ratings of how often they found themselves in good spirits as well as in a calm and relaxed state. We also aggregate a large number of deep inner reflections and growth processes that may not have surfaced for the participants without deliberate engagement in such a program. Conclusion The data indicates usefulness and effectiveness of an intervention for computer workers in terms of increasing well-being and resilience. Everyone needs a way to deliberately relax, unplug, and recover. A breathing practice is a simple way to do so, and the results call for establishing a larger body of work to make this common practice.
... Individuals who perceive a large amount of stress have an increased risk of premature death, coronary heart disease, and mental disorders such as depression or burn-out, as the World Health Organization realized as early as World Health Organization and Others (1969) and continued to investigate the problem (World Health Organization, 2005). Stress as well as the mere anticipation of stress (Hyun, Sliwinski & Smyth, 2018) also has a negative impact on the quality of products, as it increases workers error rates (Akula & Cusick, 2008). Workplace environments that are characterized by physical work have been improved over time by research on ergonomic tools as well as their placement to lessen physical strain, and alternation of tasks and restructuring of processes to counter dulling repetitive work. ...
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... Although there is a great deal more literature on the general problems of unplanned overtime in the wider workplace than there has been specific evidence focussing on software engineering projects, there is also evidence specifically concerned with software engineering professionals: A controlled study of 377 software engineers found positive correlations (p < 0.05) between unplanned overtime and several widely-used stress and depression indicators [2]. There is also evidence that the deployment of overtime can lead to increased software defect counts [3]. ...
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... As changes in technology are continuous, they result as high stress causing factor as well [17]. Software engineering job [18] is highly target demanding may also lead towards stress. Previous research studies conclude that stress among the professionals is not paid much importance or attention. ...
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... Typically, the only remaining solution open to the project manager is to fall back on the allocation of overtime. However, unplanned overtime results in bad products, as has been repeatedly demonstrated in the literature (Akula et al. 2008) (Nishikitani et al. 2005). It also has harmful effects on the engineers forced into such punitive working practices (see e.g., Kleppa et al. 2008). ...
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This document accumulates the bibliographic references utilized in the collected publications of the author over a 35-year period from 1985 to 2020. This inventory reflects over 100 research papers, articles, presentations, and multiple books covering a multi-disciplinary research background touching on over 300 keywords. The total number of bibliographic items derived from these artifacts exceeds 750 references presented in 34 separate ontological categories or topical domains. Researchers, instructors, or students looking to discover a focused yet extensive and diverse set of bibliographic references in one easy to navigate document can apply this collection to their work. Within this collection are citations ranging from Galileo in the year 1638 to a new technology publication from 2020. The topics also range widely across the following major subject areas: 1) Software Engineering, IT Operations, Cybersecurity, Quality, Reliability; 2) Management; 3) Organizational Psychology; 4) History of Science; 5) Political Economy; 6) Japanese Art, Culture, and History; and 7) Ornithology. The import, then, of this document is to not only provide useful reference information but to underscore the importance of research materials, research libraries, online research repositories, and the cycle of publication to the ongoing advancement of Science.
  • Nov 2005
  • Michael - Beck
Beck, Michael -Manage Stress to Boost Productivity, 2005 http://www.xleaders.com/Articles/Beck/Manage%20Stress%20to%20Boost%20Prod uctivity.pdf. Viewed on Oct 15 2007.
  • Oct 2005
  • Michael-Manage Beck
Beck, Michael-Manage Stress to Boost Productivity, 2005 http://www.xleaders.com/Articles/Beck/Manage%20Stress%20to%20Boost%20Prod uctivity.pdf. Viewed on Oct 15 2007.